diff --git a/pytorch/batch.py b/pytorch/batch.py index 6d98142..1bb69a6 100644 --- a/pytorch/batch.py +++ b/pytorch/batch.py @@ -16,7 +16,7 @@ parser.add_argument('base_iterations', type=int) parser.add_argument('min_time_s', type=int) parser.add_argument('baseline_time_s', type=int) parser.add_argument('baseline_delay_s', type=int) -parser.add_argument('--perf', action='store_const', const='--perf') +#parser.add_argument('--perf', action='store_const', const='--perf') parser.add_argument('--power', action='store_const', const='--power') parser.add_argument('--distribute', action='store_true') args = parser.parse_args() @@ -32,7 +32,8 @@ srun_args = { '--cpus-per-task', '160', #'--mem 28114', '--mem', '16G', - '--ntasks-per-node', '1'#, + '--ntasks-per-node', '1', + '--time', '1-00:00:00' #'--exclusive', #'--output', '/dev/null', #'--error', '/dev/null' @@ -43,6 +44,7 @@ srun_args = { '--qos', 'high', '--cpus-per-task', '16', '--ntasks-per-node', '1', + '--time', '1-00:00:00', '--prefer', 'EPYC-7313P' ], Cpu.XEON_4216: [ @@ -51,6 +53,7 @@ srun_args = { '--qos', 'tron-exempt', '--cpus-per-task', '32', '--ntasks-per-node', '1', + '--time', '1-00:00:00', '--prefer', 'Xeon,4216' ] } @@ -60,7 +63,7 @@ python = { Cpu.XEON_4216: 'python3.11' } -def srun(srun_args_list: list, run_args, matrix_file: str) -> list: +def run(run_args, matrix_file: str, srun_args_list: list = None) -> list: run_args_list = [ args.cpu.name.lower(), matrix_file, @@ -69,23 +72,30 @@ def srun(srun_args_list: list, run_args, matrix_file: str) -> list: str(args.min_time_s), str(args.baseline_time_s), str(args.baseline_delay_s)] - if args.perf is not None: - run_args_list += [args.perf] +# if args.perf is not None: +# run_args_list += [args.perf] if args.power is not None: run_args_list += [args.power] - return ['srun'] + srun_args_list + [python[args.cpu], 'run.py'] + run_args_list + + if srun_args_list is None: + command = [python[args.cpu], 'run.py'] + run_args_list + else: + command = ['srun'] + srun_args_list + [python[args.cpu], 'run.py'] + run_args_list + + print(command) + return command processes = list() for i, matrix in enumerate(glob.glob(f'{args.matrix_dir.rstrip("/")}/*.mtx')): - if args.distribute: - if args.cpu == Cpu.ALTRA: - i = i % 40 - srun_args_temp = srun_args[args.cpu] + ['--nodelist', f'oasis{i:02}'] - elif args.cpu == Cpu.EPYC_7313P: - srun_args_temp = srun_args[args.cpu] - else: - srun_args_temp = srun_args[args.cpu] + #if args.distribute: + # if args.cpu == Cpu.ALTRA: + # i = i % 40 + # srun_args_temp = srun_args[args.cpu] + ['--nodelist', f'oasis{i:02}'] + # elif args.cpu == Cpu.EPYC_7313P: + # srun_args_temp = srun_args[args.cpu] + #else: + srun_args_temp = srun_args[args.cpu] output_filename = '_'.join([ args.cpu.name.lower(), @@ -97,22 +107,29 @@ for i, matrix in enumerate(glob.glob(f'{args.matrix_dir.rstrip("/")}/*.mtx')): json_filepath = f'{args.output_dir.rstrip("/")}/{output_filename}.json' raw_filepath = f'{args.output_dir.rstrip("/")}/{output_filename}.output' with open(json_filepath, 'w') as json_file, open(raw_filepath, 'w') as raw_file: - print(srun(srun_args_temp, args, matrix)) print(json_filepath) print(raw_filepath) - processes.append(subprocess.Popen( - srun(srun_args_temp, args, matrix), - stdout=json_file, - stderr=raw_file)) + if args.distribute: + processes.append(subprocess.Popen( + run(args, matrix, srun_args_temp), + stdout=json_file, + stderr=raw_file)) + else: + subprocess.run( + run(args, matrix), + stdout=json_file, + stderr=raw_file) - # Wait on every 10 jobs to avoid socket timeout. - if i % 10 == 9: - print("Waiting on 10 jobs") - for process in processes: - process.wait() + if args.distribute: + # Wait on every 10 jobs to avoid socket timeout. + if i % 10 == 9: + print("Waiting on 10 jobs") + for process in processes: + process.wait() - processes = list() + processes = list() -for process in processes: - process.wait() +if args.distribute: + for process in processes: + process.wait() diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida.json b/pytorch/output_as-caida/altra_10_10_10_as-caida.json new file mode 100644 index 0000000..3f3c103 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 120692, "MATRIX_FILE": "as-caida", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106762, "MATRIX_DENSITY": 0.00010842726485909405, "TIME_S": 12.845242738723755, "TIME_S_1KI": 0.10642994348195203, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 724.7658282470703, "W": 70.22348643601961, "J_1KI": 6.005085906663824, "W_1KI": 0.5818404404270342, "W_D": 51.50448643601961, "J_D": 531.5699015350341, "W_D_1KI": 0.4267431680311836, "J_D_1KI": 0.0035358032680805986} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida.output b/pytorch/output_as-caida/altra_10_10_10_as-caida.output new file mode 100644 index 0000000..44a080a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106761, 106761, + 106762]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106762, layout=torch.sparse_csr) +tensor([0.0273, 0.7256, 0.4946, ..., 0.3773, 0.8985, 0.8937]) +Matrix: as-caida +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106762 +Density: 0.00010842726485909405 +Time: 12.845242738723755 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_001.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_001.json new file mode 100644 index 0000000..cb64c5c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_001.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 119741, "MATRIX_FILE": "as-caida_G_001", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 65910, "MATRIX_DENSITY": 6.693805873684353e-05, "TIME_S": 10.126415729522705, "TIME_S_1KI": 0.08456932654247672, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 934.9993497276305, "W": 78.36349396737387, "J_1KI": 7.808514625129492, "W_1KI": 0.6544416195569928, "W_D": 59.51949396737387, "J_D": 710.1608840818404, "W_D_1KI": 0.49706862283907655, "J_D_1KI": 0.004151198193092396} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_001.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_001.output new file mode 100644 index 0000000..294b387 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_001.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 148, 148, ..., 65909, 65909, 65910]), + col_indices=tensor([ 51, 111, 117, ..., 978, 8230, 12170]), + values=tensor([3., 4., 3., ..., 2., 1., 1.]), size=(31379, 31379), + nnz=65910, layout=torch.sparse_csr) +tensor([0.9176, 0.4871, 0.4502, ..., 0.9545, 0.3229, 0.4089]) +Matrix: as-caida_G_001 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 65910 +Density: 6.693805873684353e-05 +Time: 10.126415729522705 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_002.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_002.json new file mode 100644 index 0000000..821b185 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_002.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 127504, "MATRIX_FILE": "as-caida_G_002", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 66744, "MATRIX_DENSITY": 6.77850673999679e-05, "TIME_S": 11.147692203521729, "TIME_S_1KI": 0.08743013712135876, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 822.7334973049162, "W": 72.58391126827506, "J_1KI": 6.452609308766127, "W_1KI": 0.5692677191952806, "W_D": 53.68591126827506, "J_D": 608.5260047574042, "W_D_1KI": 0.42105276123317753, "J_D_1KI": 0.0033022709972485376} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_002.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_002.output new file mode 100644 index 0000000..2230fa6 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_002.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 129, 129, ..., 66743, 66743, 66744]), + col_indices=tensor([ 51, 111, 117, ..., 978, 8230, 12170]), + values=tensor([3., 4., 3., ..., 2., 1., 1.]), size=(31379, 31379), + nnz=66744, layout=torch.sparse_csr) +tensor([0.5711, 0.1553, 0.3490, ..., 0.7582, 0.3633, 0.1833]) +Matrix: as-caida_G_002 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 66744 +Density: 6.77850673999679e-05 +Time: 11.147692203521729 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_003.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_003.json new file mode 100644 index 0000000..208048f --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_003.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 143449, "MATRIX_FILE": "as-caida_G_003", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 66680, "MATRIX_DENSITY": 6.772006913325332e-05, "TIME_S": 14.305955648422241, "TIME_S_1KI": 0.09972851430419342, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 973.3464808654785, "W": 81.56949469547968, "J_1KI": 6.785313810939627, "W_1KI": 0.5686306261840771, "W_D": 62.753494695479674, "J_D": 748.8202967529297, "W_D_1KI": 0.43746205756387063, "J_D_1KI": 0.003049599910517819} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_003.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_003.output new file mode 100644 index 0000000..6bb5a01 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_003.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 89, 89, ..., 66679, 66679, 66680]), + col_indices=tensor([ 51, 111, 117, ..., 978, 978, 12170]), + values=tensor([3., 4., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=66680, layout=torch.sparse_csr) +tensor([0.2059, 0.9834, 0.9558, ..., 0.2703, 0.8687, 0.4075]) +Matrix: as-caida_G_003 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 66680 +Density: 6.772006913325332e-05 +Time: 14.305955648422241 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_004.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_004.json new file mode 100644 index 0000000..be6e164 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_004.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 103560, "MATRIX_FILE": "as-caida_G_004", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 68670, "MATRIX_DENSITY": 6.97411089889098e-05, "TIME_S": 10.448071718215942, "TIME_S_1KI": 0.10088906641768967, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 629.299670639038, "W": 68.7216518977672, "J_1KI": 6.076667348774025, "W_1KI": 0.6635926216470375, "W_D": 49.7746518977672, "J_D": 455.79771702861774, "W_D_1KI": 0.4806358815929625, "J_D_1KI": 0.004641134430214007} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_004.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_004.output new file mode 100644 index 0000000..cd9649c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_004.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 62, 62, ..., 68669, 68669, 68670]), + col_indices=tensor([ 111, 822, 875, ..., 160, 4019, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=68670, layout=torch.sparse_csr) +tensor([0.8601, 0.7413, 0.4398, ..., 0.7803, 0.6991, 0.8078]) +Matrix: as-caida_G_004 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 68670 +Density: 6.97411089889098e-05 +Time: 10.448071718215942 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_005.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_005.json new file mode 100644 index 0000000..1f43c7a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_005.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 120363, "MATRIX_FILE": "as-caida_G_005", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 70026, "MATRIX_DENSITY": 7.111825976492498e-05, "TIME_S": 10.082340002059937, "TIME_S_1KI": 0.08376610754185204, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 809.4879877853394, "W": 72.0223387430858, "J_1KI": 6.7253889300311505, "W_1KI": 0.5983760685849122, "W_D": 53.3753387430858, "J_D": 599.9068665435316, "W_D_1KI": 0.4434530440674111, "J_D_1KI": 0.003684297035363119} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_005.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_005.output new file mode 100644 index 0000000..c139a98 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_005.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 63, 63, ..., 70025, 70025, 70026]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=70026, layout=torch.sparse_csr) +tensor([0.7040, 0.6399, 0.5818, ..., 0.1186, 0.7545, 0.7756]) +Matrix: as-caida_G_005 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 70026 +Density: 7.111825976492498e-05 +Time: 10.082340002059937 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_006.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_006.json new file mode 100644 index 0000000..3367c90 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_006.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 118086, "MATRIX_FILE": "as-caida_G_006", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 71094, "MATRIX_DENSITY": 7.220291834072453e-05, "TIME_S": 10.220538854598999, "TIME_S_1KI": 0.08655165603542332, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 715.6333376598358, "W": 68.29903449226836, "J_1KI": 6.060272493435596, "W_1KI": 0.5783838430658025, "W_D": 49.44803449226836, "J_D": 518.1136487138272, "W_D_1KI": 0.4187459520372302, "J_D_1KI": 0.0035461100556986452} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_006.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_006.output new file mode 100644 index 0000000..9ff1103 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_006.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 60, 60, ..., 71093, 71093, 71094]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=71094, layout=torch.sparse_csr) +tensor([0.1653, 0.6941, 0.2553, ..., 0.0566, 0.9880, 0.5165]) +Matrix: as-caida_G_006 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 71094 +Density: 7.220291834072453e-05 +Time: 10.220538854598999 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_007.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_007.json new file mode 100644 index 0000000..730695c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_007.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 142731, "MATRIX_FILE": "as-caida_G_007", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 71658, "MATRIX_DENSITY": 7.277571556614678e-05, "TIME_S": 12.983977794647217, "TIME_S_1KI": 0.09096816945616032, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 918.3490377235412, "W": 75.87233515955411, "J_1KI": 6.434124596083129, "W_1KI": 0.5315757274842474, "W_D": 57.07933515955411, "J_D": 690.8809700853824, "W_D_1KI": 0.3999084652917314, "J_D_1KI": 0.002801833275824673} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_007.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_007.output new file mode 100644 index 0000000..bcd842e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_007.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 57, 57, ..., 71657, 71657, 71658]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=71658, layout=torch.sparse_csr) +tensor([0.9538, 0.1962, 0.6080, ..., 0.4987, 0.0086, 0.8802]) +Matrix: as-caida_G_007 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 71658 +Density: 7.277571556614678e-05 +Time: 12.983977794647217 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_008.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_008.json new file mode 100644 index 0000000..9b7eb06 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_008.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 127900, "MATRIX_FILE": "as-caida_G_008", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 72140, "MATRIX_DENSITY": 7.326523376234096e-05, "TIME_S": 12.409928798675537, "TIME_S_1KI": 0.09702837215539903, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 921.8805131340027, "W": 78.83067805993187, "J_1KI": 7.207822620281491, "W_1KI": 0.6163461928063476, "W_D": 60.15167805993187, "J_D": 703.4400971865654, "W_D_1KI": 0.4703024085999364, "J_D_1KI": 0.003677110309616391} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_008.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_008.output new file mode 100644 index 0000000..de6072c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_008.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 55, 55, ..., 72139, 72139, 72140]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=72140, layout=torch.sparse_csr) +tensor([0.0748, 0.5344, 0.1913, ..., 0.6845, 0.0381, 0.0128]) +Matrix: as-caida_G_008 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 72140 +Density: 7.326523376234096e-05 +Time: 12.409928798675537 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_009.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_009.json new file mode 100644 index 0000000..1cb1abe --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_009.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 129513, "MATRIX_FILE": "as-caida_G_009", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 74344, "MATRIX_DENSITY": 7.550361157232432e-05, "TIME_S": 10.678922891616821, "TIME_S_1KI": 0.08245444775132088, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 731.9839727020264, "W": 75.90516682079294, "J_1KI": 5.651818525569066, "W_1KI": 0.5860814498991834, "W_D": 57.05816682079294, "J_D": 550.2347913045884, "W_D_1KI": 0.4405593787557461, "J_D_1KI": 0.003401661445227476} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_009.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_009.output new file mode 100644 index 0000000..7378e27 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_009.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 38, 38, ..., 74343, 74343, 74344]), + col_indices=tensor([ 111, 875, 1040, ..., 160, 4019, 12170]), + values=tensor([4., 3., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=74344, layout=torch.sparse_csr) +tensor([0.5760, 0.2857, 0.5374, ..., 0.8141, 0.5093, 0.9535]) +Matrix: as-caida_G_009 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 74344 +Density: 7.550361157232432e-05 +Time: 10.678922891616821 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_010.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_010.json new file mode 100644 index 0000000..47ebf77 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_010.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 124622, "MATRIX_FILE": "as-caida_G_010", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 74994, "MATRIX_DENSITY": 7.616375021864427e-05, "TIME_S": 10.38208293914795, "TIME_S_1KI": 0.08330858868536815, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 957.5060850524903, "W": 71.48797724957048, "J_1KI": 7.683282927994177, "W_1KI": 0.5736385008230528, "W_D": 52.79097724957048, "J_D": 707.0794824123384, "W_D_1KI": 0.4236088110411523, "J_D_1KI": 0.0033991495164670143} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_010.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_010.output new file mode 100644 index 0000000..641547a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_010.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 28, 28, ..., 74993, 74993, 74994]), + col_indices=tensor([ 1040, 2020, 2054, ..., 160, 160, 12170]), + values=tensor([1., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=74994, layout=torch.sparse_csr) +tensor([0.1218, 0.1233, 0.3562, ..., 0.2874, 0.3356, 0.1438]) +Matrix: as-caida_G_010 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 74994 +Density: 7.616375021864427e-05 +Time: 10.38208293914795 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_011.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_011.json new file mode 100644 index 0000000..c1a537f --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_011.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 142236, "MATRIX_FILE": "as-caida_G_011", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 75118, "MATRIX_DENSITY": 7.628968436040377e-05, "TIME_S": 11.37498664855957, "TIME_S_1KI": 0.07997262752439306, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 922.4947763061523, "W": 78.68239973433768, "J_1KI": 6.485663097290083, "W_1KI": 0.5531820336225547, "W_D": 59.73639973433768, "J_D": 700.3664974164961, "W_D_1KI": 0.41998087498479764, "J_D_1KI": 0.002952704483989972} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_011.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_011.output new file mode 100644 index 0000000..628ca85 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_011.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 25, 25, ..., 75117, 75117, 75118]), + col_indices=tensor([ 1040, 2020, 2054, ..., 160, 160, 12170]), + values=tensor([1., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=75118, layout=torch.sparse_csr) +tensor([0.9968, 0.0059, 0.7418, ..., 0.5181, 0.9717, 0.5988]) +Matrix: as-caida_G_011 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 75118 +Density: 7.628968436040377e-05 +Time: 11.37498664855957 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_012.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_012.json new file mode 100644 index 0000000..4a20a9a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_012.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 108283, "MATRIX_FILE": "as-caida_G_012", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 76530, "MATRIX_DENSITY": 7.772370861979419e-05, "TIME_S": 10.989976406097412, "TIME_S_1KI": 0.10149309130793766, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 780.6230658721925, "W": 78.37336875797533, "J_1KI": 7.20910083643963, "W_1KI": 0.7237827614489377, "W_D": 59.35736875797533, "J_D": 591.2178067150118, "W_D_1KI": 0.5481688608366533, "J_D_1KI": 0.005062372309934646} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_012.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_012.output new file mode 100644 index 0000000..5513ffd --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_012.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 76530, 76530, 76530]), + col_indices=tensor([1040, 2054, 5699, ..., 160, 160, 7454]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=76530, layout=torch.sparse_csr) +tensor([0.7299, 0.6893, 0.7667, ..., 0.2441, 0.4109, 0.3491]) +Matrix: as-caida_G_012 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 76530 +Density: 7.772370861979419e-05 +Time: 10.989976406097412 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_013.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_013.json new file mode 100644 index 0000000..076c5fb --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_013.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 123279, "MATRIX_FILE": "as-caida_G_013", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 77002, "MATRIX_DENSITY": 7.820307083681422e-05, "TIME_S": 10.23405146598816, "TIME_S_1KI": 0.08301536730495995, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 676.166474685669, "W": 70.81417020223847, "J_1KI": 5.484847173368286, "W_1KI": 0.5744220037657547, "W_D": 50.85017020223847, "J_D": 485.5409619941712, "W_D_1KI": 0.412480391650147, "J_D_1KI": 0.003345909616805352} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_013.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_013.output new file mode 100644 index 0000000..d1138e1 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_013.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 5, 5, ..., 77002, 77002, 77002]), + col_indices=tensor([1040, 2054, 2150, ..., 160, 8230, 7454]), + values=tensor([1., 1., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=77002, layout=torch.sparse_csr) +tensor([0.5264, 0.1057, 0.6362, ..., 0.0751, 0.3658, 0.4784]) +Matrix: as-caida_G_013 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 77002 +Density: 7.820307083681422e-05 +Time: 10.23405146598816 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_014.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_014.json new file mode 100644 index 0000000..cc1ebe4 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_014.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 121400, "MATRIX_FILE": "as-caida_G_014", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 75982, "MATRIX_DENSITY": 7.71671609610506e-05, "TIME_S": 10.063333511352539, "TIME_S_1KI": 0.08289401574425485, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1041.4476663208006, "W": 81.6299534814742, "J_1KI": 8.578646345311371, "W_1KI": 0.6724048886447629, "W_D": 62.811953481474205, "J_D": 801.3646900482177, "W_D_1KI": 0.5173966514124728, "J_D_1KI": 0.004261916403727124} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_014.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_014.output new file mode 100644 index 0000000..b79d22c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_014.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 5, 5, ..., 75982, 75982, 75982]), + col_indices=tensor([1040, 2054, 2150, ..., 160, 160, 8230]), + values=tensor([1., 1., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=75982, layout=torch.sparse_csr) +tensor([0.6612, 0.7577, 0.1054, ..., 0.0684, 0.9601, 0.4212]) +Matrix: as-caida_G_014 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 75982 +Density: 7.71671609610506e-05 +Time: 10.063333511352539 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_015.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_015.json new file mode 100644 index 0000000..a06ce3d --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_015.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 127630, "MATRIX_FILE": "as-caida_G_015", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 77124, "MATRIX_DENSITY": 7.832697378273889e-05, "TIME_S": 12.151241302490234, "TIME_S_1KI": 0.0952067797734877, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1043.6709648132326, "W": 76.83403885753171, "J_1KI": 8.177316969468249, "W_1KI": 0.6020061024644026, "W_D": 58.006038857531706, "J_D": 787.9218565053942, "W_D_1KI": 0.4544859269570768, "J_D_1KI": 0.0035609647179901025} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_015.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_015.output new file mode 100644 index 0000000..6f16760 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_015.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 4, 4, ..., 77124, 77124, 77124]), + col_indices=tensor([1040, 2054, 4842, ..., 160, 160, 8230]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=77124, layout=torch.sparse_csr) +tensor([0.6540, 0.7414, 0.3084, ..., 0.9960, 0.8018, 0.9618]) +Matrix: as-caida_G_015 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 77124 +Density: 7.832697378273889e-05 +Time: 12.151241302490234 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_016.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_016.json new file mode 100644 index 0000000..5326f8d --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_016.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 107877, "MATRIX_FILE": "as-caida_G_016", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 77860, "MATRIX_DENSITY": 7.907445384995657e-05, "TIME_S": 11.006463050842285, "TIME_S_1KI": 0.10202789334929861, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 513.9647554016113, "W": 62.33405857814145, "J_1KI": 4.764358995908409, "W_1KI": 0.5778252878569247, "W_D": 43.50305857814145, "J_D": 358.69698478412624, "W_D_1KI": 0.4032653723976515, "J_D_1KI": 0.0037381960232269295} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_016.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_016.output new file mode 100644 index 0000000..89102d8 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_016.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 77856, 77858, 77860]), + col_indices=tensor([ 1040, 4842, 5699, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=77860, layout=torch.sparse_csr) +tensor([0.4735, 0.8183, 0.1183, ..., 0.2637, 0.0889, 0.4462]) +Matrix: as-caida_G_016 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 77860 +Density: 7.907445384995657e-05 +Time: 11.006463050842285 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_017.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_017.json new file mode 100644 index 0000000..8ca6b99 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_017.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 116896, "MATRIX_FILE": "as-caida_G_017", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 79718, "MATRIX_DENSITY": 8.096143478051423e-05, "TIME_S": 12.301311254501343, "TIME_S_1KI": 0.10523295283415467, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 661.7432917404175, "W": 69.21782114353806, "J_1KI": 5.660957532682192, "W_1KI": 0.5921316481619393, "W_D": 49.28182114353806, "J_D": 471.14910593414305, "W_D_1KI": 0.4215868904285695, "J_D_1KI": 0.0036065125447283866} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_017.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_017.output new file mode 100644 index 0000000..31fea60 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_017.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 79714, 79716, 79718]), + col_indices=tensor([ 1040, 5699, 33, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 4., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=79718, layout=torch.sparse_csr) +tensor([0.1143, 0.2051, 0.8521, ..., 0.2485, 0.3618, 0.1726]) +Matrix: as-caida_G_017 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 79718 +Density: 8.096143478051423e-05 +Time: 12.301311254501343 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_018.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_018.json new file mode 100644 index 0000000..8447a9b --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_018.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 116812, "MATRIX_FILE": "as-caida_G_018", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 80396, "MATRIX_DENSITY": 8.16500101685218e-05, "TIME_S": 10.66378378868103, "TIME_S_1KI": 0.09129013961477443, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 778.7428970146179, "W": 74.46749600000055, "J_1KI": 6.666634395563966, "W_1KI": 0.6374986816423017, "W_D": 55.170496000000554, "J_D": 576.9447637231351, "W_D_1KI": 0.4723016128479998, "J_D_1KI": 0.004043262788480634} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_018.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_018.output new file mode 100644 index 0000000..cc0d74c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_018.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 80392, 80394, 80396]), + col_indices=tensor([ 1040, 5282, 5699, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=80396, layout=torch.sparse_csr) +tensor([0.8702, 0.4804, 0.1121, ..., 0.8957, 0.0227, 0.0461]) +Matrix: as-caida_G_018 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 80396 +Density: 8.16500101685218e-05 +Time: 10.66378378868103 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_019.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_019.json new file mode 100644 index 0000000..1127c44 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_019.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 129456, "MATRIX_FILE": "as-caida_G_019", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 80970, "MATRIX_DENSITY": 8.22329633731182e-05, "TIME_S": 12.674752235412598, "TIME_S_1KI": 0.0979078006072534, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 739.2131903076173, "W": 74.1279715637925, "J_1KI": 5.710150091981966, "W_1KI": 0.5726113240312731, "W_D": 55.1819715637925, "J_D": 550.2813632507325, "W_D_1KI": 0.4262604403333372, "J_D_1KI": 0.003292705168808995} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_019.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_019.output new file mode 100644 index 0000000..7439e63 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_019.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 80966, 80968, 80970]), + col_indices=tensor([ 1040, 5699, 106, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=80970, layout=torch.sparse_csr) +tensor([0.1947, 0.2233, 0.6922, ..., 0.1662, 0.9424, 0.1964]) +Matrix: as-caida_G_019 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 80970 +Density: 8.22329633731182e-05 +Time: 12.674752235412598 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_020.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_020.json new file mode 100644 index 0000000..a6ae992 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_020.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 121477, "MATRIX_FILE": "as-caida_G_020", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 80948, "MATRIX_DENSITY": 8.221062021893506e-05, "TIME_S": 10.737972974777222, "TIME_S_1KI": 0.08839511162423522, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 957.4885776519776, "W": 79.88900379083044, "J_1KI": 7.882056501658566, "W_1KI": 0.6576471578227191, "W_D": 59.867003790830445, "J_D": 717.5201790981293, "W_D_1KI": 0.49282583362142995, "J_D_1KI": 0.004056947682453715} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_020.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_020.output new file mode 100644 index 0000000..44b164a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_020.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 80944, 80946, 80948]), + col_indices=tensor([ 1040, 5699, 106, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=80948, layout=torch.sparse_csr) +tensor([0.6576, 0.0654, 0.6667, ..., 0.9255, 0.6823, 0.1685]) +Matrix: as-caida_G_020 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 80948 +Density: 8.221062021893506e-05 +Time: 10.737972974777222 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_021.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_021.json new file mode 100644 index 0000000..fcab09f --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_021.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 101211, "MATRIX_FILE": "as-caida_G_021", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 81882, "MATRIX_DENSITY": 8.315918867380097e-05, "TIME_S": 10.29597282409668, "TIME_S_1KI": 0.10172780452813113, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 898.7896647548675, "W": 74.06007424440759, "J_1KI": 8.880355541935833, "W_1KI": 0.731739378569598, "W_D": 55.56207424440759, "J_D": 674.2987850432396, "W_D_1KI": 0.5489726832499194, "J_D_1KI": 0.005424041687661613} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_021.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_021.output new file mode 100644 index 0000000..8f8b042 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_021.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 81878, 81880, 81882]), + col_indices=tensor([ 1040, 5699, 106, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=81882, layout=torch.sparse_csr) +tensor([0.5868, 0.6239, 0.1382, ..., 0.7506, 0.4458, 0.8585]) +Matrix: as-caida_G_021 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 81882 +Density: 8.315918867380097e-05 +Time: 10.29597282409668 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_022.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_022.json new file mode 100644 index 0000000..e2dddd0 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_022.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 97313, "MATRIX_FILE": "as-caida_G_022", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 82138, "MATRIX_DENSITY": 8.341918174065929e-05, "TIME_S": 10.294092178344727, "TIME_S_1KI": 0.10578331958057738, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 537.0419758224486, "W": 67.61006796553038, "J_1KI": 5.518707426782122, "W_1KI": 0.6947691260728821, "W_D": 48.796067965530376, "J_D": 387.59814242362967, "W_D_1KI": 0.5014342170679187, "J_D_1KI": 0.005152797848878553} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_022.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_022.output new file mode 100644 index 0000000..66bbda9 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_022.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 82134, 82136, 82138]), + col_indices=tensor([ 106, 329, 1040, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=82138, layout=torch.sparse_csr) +tensor([0.5654, 0.6771, 0.6558, ..., 0.6752, 0.9803, 0.3834]) +Matrix: as-caida_G_022 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 82138 +Density: 8.341918174065929e-05 +Time: 10.294092178344727 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_023.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_023.json new file mode 100644 index 0000000..f29beca --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_023.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 140111, "MATRIX_FILE": "as-caida_G_023", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 83524, "MATRIX_DENSITY": 8.482680045419692e-05, "TIME_S": 12.064657926559448, "TIME_S_1KI": 0.08610785681751931, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 904.5556343078613, "W": 76.45920851310774, "J_1KI": 6.455992993468473, "W_1KI": 0.5457045379242724, "W_D": 57.44720851310774, "J_D": 679.6329329891205, "W_D_1KI": 0.41001212262497405, "J_D_1KI": 0.002926337850882329} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_023.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_023.output new file mode 100644 index 0000000..581ea8e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_023.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 83520, 83522, 83524]), + col_indices=tensor([ 106, 329, 1040, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=83524, layout=torch.sparse_csr) +tensor([0.6514, 0.1380, 0.8213, ..., 0.6748, 0.3381, 0.7461]) +Matrix: as-caida_G_023 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 83524 +Density: 8.482680045419692e-05 +Time: 12.064657926559448 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_024.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_024.json new file mode 100644 index 0000000..e1afba3 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_024.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 116214, "MATRIX_FILE": "as-caida_G_024", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 83640, "MATRIX_DENSITY": 8.49446098126171e-05, "TIME_S": 11.284576892852783, "TIME_S_1KI": 0.09710169938951231, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1002.3741082382203, "W": 78.47596712397663, "J_1KI": 8.625244017400831, "W_1KI": 0.6752711990291757, "W_D": 59.85396712397663, "J_D": 764.5151645679475, "W_D_1KI": 0.5150323293577076, "J_D_1KI": 0.0044317580442778635} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_024.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_024.output new file mode 100644 index 0000000..3ef8160 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_024.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 83636, 83638, 83640]), + col_indices=tensor([ 106, 329, 1040, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=83640, layout=torch.sparse_csr) +tensor([0.3311, 0.4574, 0.7903, ..., 0.2454, 0.1433, 0.1661]) +Matrix: as-caida_G_024 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 83640 +Density: 8.49446098126171e-05 +Time: 11.284576892852783 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_025.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_025.json new file mode 100644 index 0000000..836c9f3 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_025.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 115508, "MATRIX_FILE": "as-caida_G_025", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85850, "MATRIX_DENSITY": 8.718908121010495e-05, "TIME_S": 11.6570463180542, "TIME_S_1KI": 0.10091981783126883, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 777.9111336517335, "W": 74.52510352442891, "J_1KI": 6.734694857946925, "W_1KI": 0.6451943027706212, "W_D": 55.619103524428915, "J_D": 580.5657131519318, "W_D_1KI": 0.48151732801562586, "J_D_1KI": 0.004168692454337586} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_025.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_025.output new file mode 100644 index 0000000..7d9c0ba --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_025.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 85845, 85847, 85850]), + col_indices=tensor([ 346, 13811, 21783, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=85850, layout=torch.sparse_csr) +tensor([0.9169, 0.1387, 0.2857, ..., 0.8309, 0.2879, 0.8450]) +Matrix: as-caida_G_025 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85850 +Density: 8.718908121010495e-05 +Time: 11.6570463180542 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_026.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_026.json new file mode 100644 index 0000000..7b38d42 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_026.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 114440, "MATRIX_FILE": "as-caida_G_026", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85468, "MATRIX_DENSITY": 8.68011228056523e-05, "TIME_S": 11.638119459152222, "TIME_S_1KI": 0.10169625532289603, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 906.8806961631776, "W": 78.96386440870926, "J_1KI": 7.924508005620217, "W_1KI": 0.6900023104570889, "W_D": 60.217864408709254, "J_D": 691.5874647898675, "W_D_1KI": 0.5261959490449952, "J_D_1KI": 0.004598007244363817} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_026.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_026.output new file mode 100644 index 0000000..6d9f1c8 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_026.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 85463, 85465, 85468]), + col_indices=tensor([21783, 106, 329, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=85468, layout=torch.sparse_csr) +tensor([0.1366, 0.2794, 0.6490, ..., 0.4198, 0.3634, 0.1789]) +Matrix: as-caida_G_026 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85468 +Density: 8.68011228056523e-05 +Time: 11.638119459152222 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_027.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_027.json new file mode 100644 index 0000000..c2403c6 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_027.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 102448, "MATRIX_FILE": "as-caida_G_027", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85744, "MATRIX_DENSITY": 8.708142783085892e-05, "TIME_S": 10.685343265533447, "TIME_S_1KI": 0.10430016462530696, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 623.8277059173585, "W": 66.90704171784165, "J_1KI": 6.089213121948291, "W_1KI": 0.6530829466445577, "W_D": 48.12704171784165, "J_D": 448.7267895364762, "W_D_1KI": 0.4697704368835082, "J_D_1KI": 0.004585452491834962} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_027.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_027.output new file mode 100644 index 0000000..3fdabac --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_027.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 85739, 85741, 85744]), + col_indices=tensor([21783, 106, 329, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=85744, layout=torch.sparse_csr) +tensor([0.2505, 0.1829, 0.9414, ..., 0.0525, 0.8527, 0.8419]) +Matrix: as-caida_G_027 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85744 +Density: 8.708142783085892e-05 +Time: 10.685343265533447 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_028.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_028.json new file mode 100644 index 0000000..9a9fd01 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_028.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 106948, "MATRIX_FILE": "as-caida_G_028", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 84962, "MATRIX_DENSITY": 8.628723025944015e-05, "TIME_S": 10.41547679901123, "TIME_S_1KI": 0.0973882335248086, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 648.8419272613526, "W": 67.54788598351732, "J_1KI": 6.066891641371065, "W_1KI": 0.631595597706524, "W_D": 48.72688598351732, "J_D": 468.05382804584514, "W_D_1KI": 0.45561287713203913, "J_D_1KI": 0.00426013461805774} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_028.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_028.output new file mode 100644 index 0000000..7ba2788 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_028.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 84957, 84959, 84962]), + col_indices=tensor([ 1809, 21783, 106, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=84962, layout=torch.sparse_csr) +tensor([0.5564, 0.8395, 0.7950, ..., 0.7334, 0.0065, 0.6442]) +Matrix: as-caida_G_028 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 84962 +Density: 8.628723025944015e-05 +Time: 10.41547679901123 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_029.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_029.json new file mode 100644 index 0000000..d8fa6a8 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_029.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 129559, "MATRIX_FILE": "as-caida_G_029", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 86566, "MATRIX_DENSITY": 8.791624931897431e-05, "TIME_S": 13.361659049987793, "TIME_S_1KI": 0.10313184765232668, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 850.7577786254884, "W": 72.8947653550395, "J_1KI": 6.566566418585266, "W_1KI": 0.5626376041420472, "W_D": 53.7847653550395, "J_D": 627.7241894459726, "W_D_1KI": 0.41513723751371573, "J_D_1KI": 0.0032042331101175196} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_029.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_029.output new file mode 100644 index 0000000..712c7cb --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_029.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 86561, 86563, 86566]), + col_indices=tensor([ 1809, 21783, 106, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=86566, layout=torch.sparse_csr) +tensor([0.7891, 0.7339, 0.3751, ..., 0.4286, 0.1932, 0.8774]) +Matrix: as-caida_G_029 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 86566 +Density: 8.791624931897431e-05 +Time: 13.361659049987793 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_030.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_030.json new file mode 100644 index 0000000..e5227bb --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_030.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 126211, "MATRIX_FILE": "as-caida_G_030", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 86850, "MATRIX_DENSITY": 8.820467912752026e-05, "TIME_S": 10.005269289016724, "TIME_S_1KI": 0.07927414638198511, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1141.9418496513367, "W": 81.59308951543089, "J_1KI": 9.04787894598202, "W_1KI": 0.6464816023597855, "W_D": 62.695089515430894, "J_D": 877.4535553255082, "W_D_1KI": 0.4967482193741503, "J_D_1KI": 0.003935855189913322} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_030.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_030.output new file mode 100644 index 0000000..9f5d8ff --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_030.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 86850, 86850, 86850]), + col_indices=tensor([ 1809, 21783, 106, ..., 7018, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=86850, layout=torch.sparse_csr) +tensor([0.2301, 0.9372, 0.3059, ..., 0.8450, 0.5545, 0.5854]) +Matrix: as-caida_G_030 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 86850 +Density: 8.820467912752026e-05 +Time: 10.005269289016724 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_031.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_031.json new file mode 100644 index 0000000..fefd370 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_031.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 105338, "MATRIX_FILE": "as-caida_G_031", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87232, "MATRIX_DENSITY": 8.859263753197291e-05, "TIME_S": 10.614361763000488, "TIME_S_1KI": 0.10076479298069536, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 799.4572194194793, "W": 72.010733194549, "J_1KI": 7.589447487321568, "W_1KI": 0.6836159144330536, "W_D": 53.18673319454901, "J_D": 590.4747243003845, "W_D_1KI": 0.504914970803974, "J_D_1KI": 0.004793284197573278} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_031.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_031.output new file mode 100644 index 0000000..81227a4 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_031.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87232, 87232, 87232]), + col_indices=tensor([ 1809, 21783, 106, ..., 1101, 16290, 882]), + values=tensor([1., 1., 1., ..., 2., 1., 1.]), size=(31379, 31379), + nnz=87232, layout=torch.sparse_csr) +tensor([0.6837, 0.2004, 0.3302, ..., 0.8179, 0.3608, 0.2300]) +Matrix: as-caida_G_031 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87232 +Density: 8.859263753197291e-05 +Time: 10.614361763000488 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_032.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_032.json new file mode 100644 index 0000000..3ada263 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_032.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 128646, "MATRIX_FILE": "as-caida_G_032", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87938, "MATRIX_DENSITY": 8.930964966166813e-05, "TIME_S": 12.817463397979736, "TIME_S_1KI": 0.09963359449947715, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 975.9403296279908, "W": 81.64731509315205, "J_1KI": 7.586246984966426, "W_1KI": 0.634666566338262, "W_D": 62.757315093152044, "J_D": 750.1458524227144, "W_D_1KI": 0.4878295096089427, "J_D_1KI": 0.0037920301416984807} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_032.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_032.output new file mode 100644 index 0000000..b6948fb --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_032.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87938, 87938, 87938]), + col_indices=tensor([ 1809, 21783, 106, ..., 160, 16290, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87938, layout=torch.sparse_csr) +tensor([0.8667, 0.8794, 0.6030, ..., 0.3085, 0.3900, 0.2285]) +Matrix: as-caida_G_032 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87938 +Density: 8.930964966166813e-05 +Time: 12.817463397979736 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_033.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_033.json new file mode 100644 index 0000000..ef48072 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_033.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 108236, "MATRIX_FILE": "as-caida_G_033", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87784, "MATRIX_DENSITY": 8.915324758238617e-05, "TIME_S": 11.615520715713501, "TIME_S_1KI": 0.10731661106945473, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 814.9971894931793, "W": 73.68127735229483, "J_1KI": 7.529816230211568, "W_1KI": 0.6807464924082083, "W_D": 54.987277352294825, "J_D": 608.2206784462929, "W_D_1KI": 0.5080313144637165, "J_D_1KI": 0.004693736967956285} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_033.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_033.output new file mode 100644 index 0000000..234cfba --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_033.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87784, 87784, 87784]), + col_indices=tensor([ 1809, 21783, 106, ..., 160, 16290, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87784, layout=torch.sparse_csr) +tensor([0.1413, 0.0383, 0.6907, ..., 0.9449, 0.3132, 0.3976]) +Matrix: as-caida_G_033 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87784 +Density: 8.915324758238617e-05 +Time: 11.615520715713501 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_034.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_034.json new file mode 100644 index 0000000..41f550e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_034.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 118393, "MATRIX_FILE": "as-caida_G_034", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88490, "MATRIX_DENSITY": 8.987025971208138e-05, "TIME_S": 10.513860940933228, "TIME_S_1KI": 0.0888047514712291, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 818.8505859184265, "W": 73.52922556303459, "J_1KI": 6.916376693879085, "W_1KI": 0.6210605826614292, "W_D": 54.69022556303459, "J_D": 609.0520184781552, "W_D_1KI": 0.4619379994005945, "J_D_1KI": 0.0039017340501600137} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_034.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_034.output new file mode 100644 index 0000000..4b9a2a7 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_034.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 88489, 88489, 88490]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88490, layout=torch.sparse_csr) +tensor([0.8060, 0.0837, 0.1341, ..., 0.3387, 0.8994, 0.6830]) +Matrix: as-caida_G_034 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88490 +Density: 8.987025971208138e-05 +Time: 10.513860940933228 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_035.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_035.json new file mode 100644 index 0000000..4369f3d --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_035.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 139029, "MATRIX_FILE": "as-caida_G_035", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87560, "MATRIX_DENSITY": 8.892575364888514e-05, "TIME_S": 13.630029678344727, "TIME_S_1KI": 0.0980373136420799, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 946.0831095790862, "W": 76.8712422214838, "J_1KI": 6.804933571982005, "W_1KI": 0.5529151631780693, "W_D": 57.994242221483795, "J_D": 713.7568150713442, "W_D_1KI": 0.4171377354471642, "J_D_1KI": 0.003000364927081143} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_035.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_035.output new file mode 100644 index 0000000..0c3d57b --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_035.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87559, 87559, 87560]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87560, layout=torch.sparse_csr) +tensor([0.2258, 0.9079, 0.9180, ..., 0.7245, 0.2460, 0.3925]) +Matrix: as-caida_G_035 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87560 +Density: 8.892575364888514e-05 +Time: 13.630029678344727 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_036.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_036.json new file mode 100644 index 0000000..1d3e20e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_036.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 130613, "MATRIX_FILE": "as-caida_G_036", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88616, "MATRIX_DENSITY": 8.999822504967571e-05, "TIME_S": 12.590465784072876, "TIME_S_1KI": 0.09639519637457891, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 851.3253401374816, "W": 78.82016710712844, "J_1KI": 6.517921953691299, "W_1KI": 0.6034634156410804, "W_D": 60.08416710712844, "J_D": 648.9604865951537, "W_D_1KI": 0.4600167449421454, "J_D_1KI": 0.0035219828419999957} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_036.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_036.output new file mode 100644 index 0000000..7fd0bac --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_036.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 88615, 88615, 88616]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88616, layout=torch.sparse_csr) +tensor([0.1612, 0.9891, 0.1530, ..., 0.9514, 0.9568, 0.3072]) +Matrix: as-caida_G_036 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88616 +Density: 8.999822504967571e-05 +Time: 12.590465784072876 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_037.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_037.json new file mode 100644 index 0000000..f7fb8bc --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_037.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 138339, "MATRIX_FILE": "as-caida_G_037", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88654, "MATRIX_DENSITY": 9.003681777053749e-05, "TIME_S": 12.654316425323486, "TIME_S_1KI": 0.09147323911061585, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 888.2931414222718, "W": 75.51405609798103, "J_1KI": 6.421133168681802, "W_1KI": 0.5458623822492648, "W_D": 56.56405609798102, "J_D": 665.3789463734628, "W_D_1KI": 0.4088800417668266, "J_D_1KI": 0.0029556382637349306} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_037.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_037.output new file mode 100644 index 0000000..a1c28d9 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_037.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 88653, 88653, 88654]), + col_indices=tensor([ 1809, 106, 329, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88654, layout=torch.sparse_csr) +tensor([0.8026, 0.1152, 0.4121, ..., 0.0272, 0.6179, 0.0032]) +Matrix: as-caida_G_037 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88654 +Density: 9.003681777053749e-05 +Time: 12.654316425323486 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_038.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_038.json new file mode 100644 index 0000000..403e3ed --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_038.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 127019, "MATRIX_FILE": "as-caida_G_038", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88644, "MATRIX_DENSITY": 9.002666179136334e-05, "TIME_S": 12.376951217651367, "TIME_S_1KI": 0.0974417309036551, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1144.6182090759278, "W": 77.91927208125107, "J_1KI": 9.01139364249386, "W_1KI": 0.6134458000870032, "W_D": 59.13827208125106, "J_D": 868.7291509461402, "W_D_1KI": 0.46558603107606783, "J_D_1KI": 0.003665483361355922} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_038.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_038.output new file mode 100644 index 0000000..e6b67ad --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_038.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 88643, 88643, 88644]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88644, layout=torch.sparse_csr) +tensor([0.2941, 0.4961, 0.4501, ..., 0.6791, 0.6484, 0.8779]) +Matrix: as-caida_G_038 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88644 +Density: 9.002666179136334e-05 +Time: 12.376951217651367 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_039.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_039.json new file mode 100644 index 0000000..f61e551 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_039.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 141833, "MATRIX_FILE": "as-caida_G_039", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87804, "MATRIX_DENSITY": 8.917355954073447e-05, "TIME_S": 12.296685218811035, "TIME_S_1KI": 0.0866983369089777, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1033.3566898822785, "W": 80.89532252127742, "J_1KI": 7.285728214747474, "W_1KI": 0.5703561408224984, "W_D": 61.89832252127742, "J_D": 790.6890494568347, "W_D_1KI": 0.43641693062458964, "J_D_1KI": 0.0030769773651025474} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_039.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_039.output new file mode 100644 index 0000000..4539380 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_039.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 87803, 87803, 87804]), + col_indices=tensor([ 1809, 106, 329, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87804, layout=torch.sparse_csr) +tensor([0.1788, 0.5284, 0.8814, ..., 0.5648, 0.9765, 0.7499]) +Matrix: as-caida_G_039 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87804 +Density: 8.917355954073447e-05 +Time: 12.296685218811035 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_040.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_040.json new file mode 100644 index 0000000..397bba6 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_040.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 126480, "MATRIX_FILE": "as-caida_G_040", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89658, "MATRIX_DENSITY": 9.105647807962247e-05, "TIME_S": 10.94791579246521, "TIME_S_1KI": 0.0865584740074732, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1060.2959427833557, "W": 82.28098111370639, "J_1KI": 8.383111502082192, "W_1KI": 0.650545391474592, "W_D": 63.29598111370639, "J_D": 815.6498751103878, "W_D_1KI": 0.5004426084258886, "J_D_1KI": 0.003956693615005445} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_040.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_040.output new file mode 100644 index 0000000..063ecb0 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_040.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89657, 89657, 89658]), + col_indices=tensor([ 106, 329, 1040, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89658, layout=torch.sparse_csr) +tensor([0.5503, 0.9498, 0.7790, ..., 0.0188, 0.3119, 0.2062]) +Matrix: as-caida_G_040 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89658 +Density: 9.105647807962247e-05 +Time: 10.94791579246521 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_041.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_041.json new file mode 100644 index 0000000..9c8f025 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_041.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 105131, "MATRIX_FILE": "as-caida_G_041", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88944, "MATRIX_DENSITY": 9.033134116658794e-05, "TIME_S": 13.39965295791626, "TIME_S_1KI": 0.12745672501846517, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 743.1411743736267, "W": 70.18952496371918, "J_1KI": 7.068715929398814, "W_1KI": 0.6676387075526646, "W_D": 51.187524963719184, "J_D": 541.9549061555863, "W_D_1KI": 0.4868927810419304, "J_D_1KI": 0.004631296012041456} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_041.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_041.output new file mode 100644 index 0000000..b016c0a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_041.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 88943, 88943, 88944]), + col_indices=tensor([ 106, 329, 1040, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88944, layout=torch.sparse_csr) +tensor([0.4738, 0.4885, 0.1707, ..., 0.1175, 0.9603, 0.6544]) +Matrix: as-caida_G_041 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88944 +Density: 9.033134116658794e-05 +Time: 13.39965295791626 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_042.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_042.json new file mode 100644 index 0000000..a3e62b1 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_042.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 115909, "MATRIX_FILE": "as-caida_G_042", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89176, "MATRIX_DENSITY": 9.056695988342829e-05, "TIME_S": 11.162479877471924, "TIME_S_1KI": 0.09630382349491345, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 797.8189125061035, "W": 71.99675341775847, "J_1KI": 6.883148957424389, "W_1KI": 0.6211489480347383, "W_D": 53.25075341775847, "J_D": 590.0885271224976, "W_D_1KI": 0.45941862510899467, "J_D_1KI": 0.003963614776324485} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_042.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_042.output new file mode 100644 index 0000000..71f8fc2 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_042.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89173, 89173, 89176]), + col_indices=tensor([ 106, 329, 1040, ..., 2232, 5295, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=89176, layout=torch.sparse_csr) +tensor([0.8462, 0.1475, 0.5030, ..., 0.4659, 0.2643, 0.5823]) +Matrix: as-caida_G_042 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89176 +Density: 9.056695988342829e-05 +Time: 11.162479877471924 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_043.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_043.json new file mode 100644 index 0000000..3039627 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_043.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 130909, "MATRIX_FILE": "as-caida_G_043", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89678, "MATRIX_DENSITY": 9.107679003797077e-05, "TIME_S": 12.607298135757446, "TIME_S_1KI": 0.09630581652718642, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 920.6237554645538, "W": 74.85525467413538, "J_1KI": 7.032547460178856, "W_1KI": 0.5718113702964303, "W_D": 56.03525467413538, "J_D": 689.1618607282638, "W_D_1KI": 0.42804738157143807, "J_D_1KI": 0.0032698086577044976} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_043.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_043.output new file mode 100644 index 0000000..b5a43d5 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_043.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89676, 89676, 89678]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89678, layout=torch.sparse_csr) +tensor([0.4155, 0.5214, 0.2516, ..., 0.2688, 0.8252, 0.1018]) +Matrix: as-caida_G_043 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89678 +Density: 9.107679003797077e-05 +Time: 12.607298135757446 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_044.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_044.json new file mode 100644 index 0000000..1d4c12f --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_044.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 106563, "MATRIX_FILE": "as-caida_G_044", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89560, "MATRIX_DENSITY": 9.095694948371577e-05, "TIME_S": 12.652342557907104, "TIME_S_1KI": 0.11873110327137097, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 621.244135837555, "W": 66.15231158833835, "J_1KI": 5.829829639157634, "W_1KI": 0.6207812429111262, "W_D": 47.27031158833835, "J_D": 443.9210538282395, "W_D_1KI": 0.44359028544934315, "J_D_1KI": 0.004162704554576571} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_044.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_044.output new file mode 100644 index 0000000..b19e085 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_044.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 89559, 89559, 89560]), + col_indices=tensor([ 5326, 106, 329, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89560, layout=torch.sparse_csr) +tensor([0.4404, 0.2775, 0.5687, ..., 0.1114, 0.2519, 0.8574]) +Matrix: as-caida_G_044 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89560 +Density: 9.095694948371577e-05 +Time: 12.652342557907104 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_045.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_045.json new file mode 100644 index 0000000..8cd9597 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_045.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 122630, "MATRIX_FILE": "as-caida_G_045", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89152, "MATRIX_DENSITY": 9.054258553341032e-05, "TIME_S": 12.735206127166748, "TIME_S_1KI": 0.10385065748321576, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1027.8703737640383, "W": 77.18248362128287, "J_1KI": 8.381883501296896, "W_1KI": 0.6293931633473283, "W_D": 58.48148362128287, "J_D": 778.8215875902177, "W_D_1KI": 0.4768937749431858, "J_D_1KI": 0.0038888834293662705} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_045.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_045.output new file mode 100644 index 0000000..d9ab44e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_045.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89150, 89150, 89152]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89152, layout=torch.sparse_csr) +tensor([0.4846, 0.9604, 0.9616, ..., 0.8396, 0.3019, 0.8305]) +Matrix: as-caida_G_045 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89152 +Density: 9.054258553341032e-05 +Time: 12.735206127166748 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_046.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_046.json new file mode 100644 index 0000000..f37f543 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_046.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 113074, "MATRIX_FILE": "as-caida_G_046", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90172, "MATRIX_DENSITY": 9.157849540917394e-05, "TIME_S": 10.500521898269653, "TIME_S_1KI": 0.09286415885411017, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 758.198433933258, "W": 73.8415920062998, "J_1KI": 6.705329553507066, "W_1KI": 0.6530377629366593, "W_D": 55.064592006299804, "J_D": 565.3979862837791, "W_D_1KI": 0.4869783682040063, "J_D_1KI": 0.004306722749739165} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_046.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_046.output new file mode 100644 index 0000000..1f27d02 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_046.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 90170, 90170, 90172]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90172, layout=torch.sparse_csr) +tensor([0.3790, 0.3032, 0.0405, ..., 0.0113, 0.1281, 0.2860]) +Matrix: as-caida_G_046 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90172 +Density: 9.157849540917394e-05 +Time: 10.500521898269653 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_047.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_047.json new file mode 100644 index 0000000..b0562e9 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_047.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 126496, "MATRIX_FILE": "as-caida_G_047", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90002, "MATRIX_DENSITY": 9.140584376321335e-05, "TIME_S": 10.600306034088135, "TIME_S_1KI": 0.08379953543264715, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1235.8763800144193, "W": 78.10613100977226, "J_1KI": 9.770082690475741, "W_1KI": 0.6174592952328316, "W_D": 59.286131009772255, "J_D": 938.0867805147168, "W_D_1KI": 0.4686798871883084, "J_D_1KI": 0.0037050965025637837} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_047.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_047.output new file mode 100644 index 0000000..879242b --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_047.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90000, 90000, 90002]), + col_indices=tensor([ 5326, 106, 329, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90002, layout=torch.sparse_csr) +tensor([0.5848, 0.1698, 0.4450, ..., 0.6169, 0.4741, 0.5274]) +Matrix: as-caida_G_047 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90002 +Density: 9.140584376321335e-05 +Time: 10.600306034088135 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_048.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_048.json new file mode 100644 index 0000000..5d2a545 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_048.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 123716, "MATRIX_FILE": "as-caida_G_048", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90820, "MATRIX_DENSITY": 9.223660285965907e-05, "TIME_S": 10.587847232818604, "TIME_S_1KI": 0.08558187488132984, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 737.9514087200165, "W": 72.62112727115486, "J_1KI": 5.964882543244338, "W_1KI": 0.5869986684919886, "W_D": 53.34112727115486, "J_D": 542.0345496082307, "W_D_1KI": 0.4311578718286629, "J_D_1KI": 0.003485061526630855} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_048.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_048.output new file mode 100644 index 0000000..3d2fef1 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_048.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 90816, 90816, 90820]), + col_indices=tensor([ 106, 329, 1040, ..., 3562, 13498, 16085]), + values=tensor([1., 1., 1., ..., 3., 3., 3.]), size=(31379, 31379), + nnz=90820, layout=torch.sparse_csr) +tensor([0.6448, 0.2976, 0.8562, ..., 0.0284, 0.6709, 0.2386]) +Matrix: as-caida_G_048 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90820 +Density: 9.223660285965907e-05 +Time: 10.587847232818604 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_049.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_049.json new file mode 100644 index 0000000..b57d460 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_049.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 132716, "MATRIX_FILE": "as-caida_G_049", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90784, "MATRIX_DENSITY": 9.220004133463212e-05, "TIME_S": 12.987859964370728, "TIME_S_1KI": 0.09786205102904492, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1069.818884792328, "W": 76.0638705536987, "J_1KI": 8.060963898793876, "W_1KI": 0.573132633244663, "W_D": 57.34087055369871, "J_D": 806.484678497553, "W_D_1KI": 0.4320569528444099, "J_D_1KI": 0.003255500111850944} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_049.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_049.output new file mode 100644 index 0000000..215d1ff --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_049.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90780, 90780, 90784]), + col_indices=tensor([ 5326, 106, 329, ..., 3562, 13498, 16085]), + values=tensor([1., 1., 1., ..., 3., 3., 3.]), size=(31379, 31379), + nnz=90784, layout=torch.sparse_csr) +tensor([0.2745, 0.9273, 0.0601, ..., 0.0658, 0.0880, 0.4539]) +Matrix: as-caida_G_049 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90784 +Density: 9.220004133463212e-05 +Time: 12.987859964370728 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_050.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_050.json new file mode 100644 index 0000000..9234532 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_050.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 127691, "MATRIX_FILE": "as-caida_G_050", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90392, "MATRIX_DENSITY": 9.180192695100532e-05, "TIME_S": 14.814650774002075, "TIME_S_1KI": 0.11601953758684697, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 929.225703086853, "W": 75.02660242711305, "J_1KI": 7.277143284075252, "W_1KI": 0.5875637470699817, "W_D": 56.48860242711305, "J_D": 699.6273269567489, "W_D_1KI": 0.4423851518675008, "J_D_1KI": 0.003464497512491098} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_050.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_050.output new file mode 100644 index 0000000..5c7fbe8 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_050.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90390, 90390, 90392]), + col_indices=tensor([ 5326, 106, 329, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90392, layout=torch.sparse_csr) +tensor([0.4219, 0.7062, 0.3153, ..., 0.4054, 0.6358, 0.0801]) +Matrix: as-caida_G_050 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90392 +Density: 9.180192695100532e-05 +Time: 14.814650774002075 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_051.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_051.json new file mode 100644 index 0000000..5232d01 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_051.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 147759, "MATRIX_FILE": "as-caida_G_051", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90100, "MATRIX_DENSITY": 9.150537235912004e-05, "TIME_S": 13.691451787948608, "TIME_S_1KI": 0.09266069605200772, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1070.7594993400573, "W": 80.64166503228896, "J_1KI": 7.2466617894006955, "W_1KI": 0.5457648267265545, "W_D": 61.55766503228895, "J_D": 817.3622725191115, "W_D_1KI": 0.4166085655174233, "J_D_1KI": 0.0028195139755779566} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_051.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_051.output new file mode 100644 index 0000000..7ddb2a7 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_051.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90098, 90098, 90100]), + col_indices=tensor([ 5326, 106, 329, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90100, layout=torch.sparse_csr) +tensor([0.0219, 0.4547, 0.8406, ..., 0.7553, 0.4269, 0.9394]) +Matrix: as-caida_G_051 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90100 +Density: 9.150537235912004e-05 +Time: 13.691451787948608 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_052.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_052.json new file mode 100644 index 0000000..3f7103b --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_052.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 121520, "MATRIX_FILE": "as-caida_G_052", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 91100, "MATRIX_DENSITY": 9.252097027653536e-05, "TIME_S": 10.23447299003601, "TIME_S_1KI": 0.08422048214315347, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 730.5792516517639, "W": 73.90907253151698, "J_1KI": 6.012008324981599, "W_1KI": 0.6082050076655446, "W_D": 54.978072531516986, "J_D": 543.4493724732398, "W_D_1KI": 0.4524199517076776, "J_D_1KI": 0.003723008160859757} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_052.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_052.output new file mode 100644 index 0000000..5f343c5 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_052.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 91097, 91097, 91100]), + col_indices=tensor([ 106, 329, 1040, ..., 2232, 16085, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=91100, layout=torch.sparse_csr) +tensor([0.3609, 0.6866, 0.9245, ..., 0.9386, 0.9964, 0.2117]) +Matrix: as-caida_G_052 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 91100 +Density: 9.252097027653536e-05 +Time: 10.23447299003601 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_053.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_053.json new file mode 100644 index 0000000..91a9ccd --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_053.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 134102, "MATRIX_FILE": "as-caida_G_053", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90296, "MATRIX_DENSITY": 9.170442955093344e-05, "TIME_S": 13.314124584197998, "TIME_S_1KI": 0.09928356463138506, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1508.8533783626556, "W": 82.48007828777826, "J_1KI": 11.25153523707816, "W_1KI": 0.61505479625791, "W_D": 63.581078287778254, "J_D": 1163.1235901563166, "W_D_1KI": 0.4741247579288769, "J_D_1KI": 0.0035355532201523984} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_053.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_053.output new file mode 100644 index 0000000..a995a61 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_053.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90294, 90294, 90296]), + col_indices=tensor([21783, 106, 329, ..., 160, 16085, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90296, layout=torch.sparse_csr) +tensor([0.6348, 0.4878, 0.9893, ..., 0.9716, 0.1087, 0.3217]) +Matrix: as-caida_G_053 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90296 +Density: 9.170442955093344e-05 +Time: 13.314124584197998 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_054.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_054.json new file mode 100644 index 0000000..2fdaa84 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_054.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 108821, "MATRIX_FILE": "as-caida_G_054", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92170, "MATRIX_DENSITY": 9.360766004816975e-05, "TIME_S": 10.534549474716187, "TIME_S_1KI": 0.09680621823651855, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 630.309701499939, "W": 66.16591062434298, "J_1KI": 5.792169723674098, "W_1KI": 0.6080252030797638, "W_D": 47.268910624342986, "J_D": 450.29309904026996, "W_D_1KI": 0.434373058732625, "J_D_1KI": 0.003991628993784517} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_054.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_054.output new file mode 100644 index 0000000..e5f7358 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_054.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 92169, 92169, 92170]), + col_indices=tensor([21783, 106, 329, ..., 155, 160, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92170, layout=torch.sparse_csr) +tensor([0.0747, 0.6882, 0.4968, ..., 0.9101, 0.5697, 0.6986]) +Matrix: as-caida_G_054 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92170 +Density: 9.360766004816975e-05 +Time: 10.534549474716187 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_055.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_055.json new file mode 100644 index 0000000..751e5cc --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_055.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 119676, "MATRIX_FILE": "as-caida_G_055", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 91476, "MATRIX_DENSITY": 9.290283509348351e-05, "TIME_S": 13.72050166130066, "TIME_S_1KI": 0.11464706090862545, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 561.1543012332917, "W": 65.8719091639173, "J_1KI": 4.688945997804837, "W_1KI": 0.5504187068745388, "W_D": 46.566909163917295, "J_D": 396.69749524712574, "W_D_1KI": 0.3891081684207134, "J_D_1KI": 0.0032513467062795665} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_055.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_055.output new file mode 100644 index 0000000..139c347 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_055.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 91475, 91475, 91476]), + col_indices=tensor([21783, 106, 329, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=91476, layout=torch.sparse_csr) +tensor([0.0054, 0.2558, 0.4052, ..., 0.3463, 0.3352, 0.4116]) +Matrix: as-caida_G_055 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 91476 +Density: 9.290283509348351e-05 +Time: 13.72050166130066 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_056.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_056.json new file mode 100644 index 0000000..c256404 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_056.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 134998, "MATRIX_FILE": "as-caida_G_056", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92826, "MATRIX_DENSITY": 9.427389228199419e-05, "TIME_S": 11.813426971435547, "TIME_S_1KI": 0.08750816287230587, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1077.9362324142455, "W": 78.36027178297793, "J_1KI": 7.9848311264925815, "W_1KI": 0.5804550569858659, "W_D": 59.53727178297793, "J_D": 819.0040817074776, "W_D_1KI": 0.44102336170149137, "J_D_1KI": 0.0032668881146497826} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_056.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_056.output new file mode 100644 index 0000000..9195bd6 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_056.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 92825, 92825, 92826]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92826, layout=torch.sparse_csr) +tensor([0.5038, 0.5548, 0.3018, ..., 0.4538, 0.8409, 0.8807]) +Matrix: as-caida_G_056 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92826 +Density: 9.427389228199419e-05 +Time: 11.813426971435547 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_057.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_057.json new file mode 100644 index 0000000..e64c3df --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_057.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 122251, "MATRIX_FILE": "as-caida_G_057", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92334, "MATRIX_DENSITY": 9.377421810662586e-05, "TIME_S": 10.217139720916748, "TIME_S_1KI": 0.08357510139726258, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 986.8290935611724, "W": 84.76703621612427, "J_1KI": 8.072155594319657, "W_1KI": 0.6933852174307308, "W_D": 65.94903621612427, "J_D": 767.7563182044029, "W_D_1KI": 0.5394560062177346, "J_D_1KI": 0.004412691971580883} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_057.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_057.output new file mode 100644 index 0000000..6196a48 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_057.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 92333, 92333, 92334]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92334, layout=torch.sparse_csr) +tensor([0.5507, 0.1647, 0.0740, ..., 0.2884, 0.3198, 0.5228]) +Matrix: as-caida_G_057 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92334 +Density: 9.377421810662586e-05 +Time: 10.217139720916748 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_058.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_058.json new file mode 100644 index 0000000..e76f17e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_058.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 117107, "MATRIX_FILE": "as-caida_G_058", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92170, "MATRIX_DENSITY": 9.360766004816975e-05, "TIME_S": 10.773444175720215, "TIME_S_1KI": 0.09199658582083237, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 859.3447602748871, "W": 74.41766840535198, "J_1KI": 7.3381160842211575, "W_1KI": 0.635467294058869, "W_D": 55.61666840535197, "J_D": 642.2385113942623, "W_D_1KI": 0.47492181001436273, "J_D_1KI": 0.004055451937239983} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_058.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_058.output new file mode 100644 index 0000000..7e849c6 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_058.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 92169, 92169, 92170]), + col_indices=tensor([ 996, 25003, 106, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92170, layout=torch.sparse_csr) +tensor([0.1517, 0.6402, 0.6059, ..., 0.3739, 0.1179, 0.6419]) +Matrix: as-caida_G_058 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92170 +Density: 9.360766004816975e-05 +Time: 10.773444175720215 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_059.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_059.json new file mode 100644 index 0000000..c3b8b08 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_059.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 143936, "MATRIX_FILE": "as-caida_G_059", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93156, "MATRIX_DENSITY": 9.460903959474125e-05, "TIME_S": 12.087766885757446, "TIME_S_1KI": 0.08398015010669635, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 936.0070211696624, "W": 78.92449837101914, "J_1KI": 6.502938953212972, "W_1KI": 0.5483304966861601, "W_D": 60.176498371019136, "J_D": 713.6646560602186, "W_D_1KI": 0.4180781623153286, "J_D_1KI": 0.0029046115100831525} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_059.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_059.output new file mode 100644 index 0000000..0bc6dfc --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_059.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 93155, 93155, 93156]), + col_indices=tensor([ 996, 25003, 106, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93156, layout=torch.sparse_csr) +tensor([0.5154, 0.7993, 0.3854, ..., 0.3839, 0.5008, 0.0115]) +Matrix: as-caida_G_059 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93156 +Density: 9.460903959474125e-05 +Time: 12.087766885757446 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_060.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_060.json new file mode 100644 index 0000000..1f3e5c1 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_060.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 83178, "MATRIX_FILE": "as-caida_G_060", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94180, "MATRIX_DENSITY": 9.564901186217454e-05, "TIME_S": 12.326122045516968, "TIME_S_1KI": 0.14818969012860334, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 467.98362459182744, "W": 69.55048173154363, "J_1KI": 5.62629090134203, "W_1KI": 0.8361643912037273, "W_D": 51.030481731543624, "J_D": 343.36828747749337, "W_D_1KI": 0.6135093622297196, "J_D_1KI": 0.007375860951570363} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_060.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_060.output new file mode 100644 index 0000000..2b7eec4 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_060.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94180, 94180, 94180]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94180, layout=torch.sparse_csr) +tensor([0.3204, 0.2470, 0.8909, ..., 0.4323, 0.4024, 0.8540]) +Matrix: as-caida_G_060 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94180 +Density: 9.564901186217454e-05 +Time: 12.326122045516968 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_061.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_061.json new file mode 100644 index 0000000..0c82549 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_061.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 116912, "MATRIX_FILE": "as-caida_G_061", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94386, "MATRIX_DENSITY": 9.58582250331621e-05, "TIME_S": 10.325057983398438, "TIME_S_1KI": 0.08831478362698814, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 638.1425363731383, "W": 66.57023625217482, "J_1KI": 5.458315111991398, "W_1KI": 0.5694046483866055, "W_D": 47.779236252174826, "J_D": 458.01193933629986, "W_D_1KI": 0.4086769215493262, "J_D_1KI": 0.003495594306395633} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_061.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_061.output new file mode 100644 index 0000000..ca69f11 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_061.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94386, 94386, 94386]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94386, layout=torch.sparse_csr) +tensor([0.5902, 0.7895, 0.0352, ..., 0.8265, 0.1453, 0.8822]) +Matrix: as-caida_G_061 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94386 +Density: 9.58582250331621e-05 +Time: 10.325057983398438 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_062.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_062.json new file mode 100644 index 0000000..1c00bcf --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_062.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 115657, "MATRIX_FILE": "as-caida_G_062", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93728, "MATRIX_DENSITY": 9.518996160350281e-05, "TIME_S": 12.241574048995972, "TIME_S_1KI": 0.10584377987494031, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 747.6433933258056, "W": 67.45654289666983, "J_1KI": 6.464315980232979, "W_1KI": 0.5832465211502099, "W_D": 48.52854289666983, "J_D": 537.858047958374, "W_D_1KI": 0.41959019252332186, "J_D_1KI": 0.0036278841101128495} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_062.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_062.output new file mode 100644 index 0000000..5d9602c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_062.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93728, 93728, 93728]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93728, layout=torch.sparse_csr) +tensor([0.1401, 0.4454, 0.5344, ..., 0.1357, 0.4708, 0.2697]) +Matrix: as-caida_G_062 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93728 +Density: 9.518996160350281e-05 +Time: 12.241574048995972 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_063.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_063.json new file mode 100644 index 0000000..2e09324 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_063.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 103117, "MATRIX_FILE": "as-caida_G_063", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94736, "MATRIX_DENSITY": 9.621368430425745e-05, "TIME_S": 11.914648294448853, "TIME_S_1KI": 0.11554494694811576, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 489.15072479248045, "W": 69.94763121734192, "J_1KI": 4.743647747631142, "W_1KI": 0.6783326824611066, "W_D": 50.98463121734192, "J_D": 356.5405844230651, "W_D_1KI": 0.4944347800783762, "J_D_1KI": 0.004794891046853344} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_063.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_063.output new file mode 100644 index 0000000..4431780 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_063.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94736, 94736, 94736]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94736, layout=torch.sparse_csr) +tensor([0.6187, 0.0124, 0.2936, ..., 0.7837, 0.9441, 0.3856]) +Matrix: as-caida_G_063 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94736 +Density: 9.621368430425745e-05 +Time: 11.914648294448853 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_064.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_064.json new file mode 100644 index 0000000..720a34b --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_064.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 119351, "MATRIX_FILE": "as-caida_G_064", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93558, "MATRIX_DENSITY": 9.50173099575422e-05, "TIME_S": 11.515212297439575, "TIME_S_1KI": 0.09648190880210115, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 661.508429031372, "W": 65.61552845714954, "J_1KI": 5.542546179180501, "W_1KI": 0.5497694066840625, "W_D": 46.735528457149535, "J_D": 471.16813255310046, "W_D_1KI": 0.3915805352041418, "J_D_1KI": 0.0032809154108817003} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_064.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_064.output new file mode 100644 index 0000000..6cc28ff --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_064.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93558, 93558, 93558]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93558, layout=torch.sparse_csr) +tensor([0.7807, 0.8530, 0.7477, ..., 0.2225, 0.0885, 0.8388]) +Matrix: as-caida_G_064 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93558 +Density: 9.50173099575422e-05 +Time: 11.515212297439575 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_065.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_065.json new file mode 100644 index 0000000..634746a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_065.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 132958, "MATRIX_FILE": "as-caida_G_065", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 95068, "MATRIX_DENSITY": 9.655086281283934e-05, "TIME_S": 13.409671783447266, "TIME_S_1KI": 0.10085644928057932, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 989.7945313262941, "W": 75.65144512001795, "J_1KI": 7.44441501320939, "W_1KI": 0.5689875383205069, "W_D": 56.449445120017955, "J_D": 738.5629182305337, "W_D_1KI": 0.42456599166667636, "J_D_1KI": 0.0031932338909029644} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_065.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_065.output new file mode 100644 index 0000000..c9a1601 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_065.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 95068, 95068, 95068]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=95068, layout=torch.sparse_csr) +tensor([0.9310, 0.8874, 0.3304, ..., 0.1175, 0.6004, 0.3426]) +Matrix: as-caida_G_065 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 95068 +Density: 9.655086281283934e-05 +Time: 13.409671783447266 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_066.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_066.json new file mode 100644 index 0000000..7a2ba1c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_066.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 119218, "MATRIX_FILE": "as-caida_G_066", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93212, "MATRIX_DENSITY": 9.466591307811651e-05, "TIME_S": 12.01876187324524, "TIME_S_1KI": 0.10081331571780468, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 817.2109241867065, "W": 75.97251627046325, "J_1KI": 6.854761228897536, "W_1KI": 0.6372570943185025, "W_D": 57.00751627046324, "J_D": 613.2107681035994, "W_D_1KI": 0.4781787672202456, "J_D_1KI": 0.0040109611570421045} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_066.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_066.output new file mode 100644 index 0000000..8e8bf47 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_066.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93212, 93212, 93212]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93212, layout=torch.sparse_csr) +tensor([0.6634, 0.7808, 0.6440, ..., 0.2826, 0.0426, 0.9971]) +Matrix: as-caida_G_066 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93212 +Density: 9.466591307811651e-05 +Time: 12.01876187324524 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_067.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_067.json new file mode 100644 index 0000000..e1149f7 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_067.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 138530, "MATRIX_FILE": "as-caida_G_067", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94484, "MATRIX_DENSITY": 9.59577536290688e-05, "TIME_S": 12.678122520446777, "TIME_S_1KI": 0.09151896715835399, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 930.2989678955078, "W": 79.01238289331735, "J_1KI": 6.715505434891416, "W_1KI": 0.5703629747586613, "W_D": 60.10438289331735, "J_D": 707.6744596748351, "W_D_1KI": 0.4338726838469454, "J_D_1KI": 0.0031319763505879257} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_067.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_067.output new file mode 100644 index 0000000..225f597 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_067.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94484, 94484, 94484]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94484, layout=torch.sparse_csr) +tensor([0.1763, 0.4292, 0.1923, ..., 0.7323, 0.0202, 0.5947]) +Matrix: as-caida_G_067 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94484 +Density: 9.59577536290688e-05 +Time: 12.678122520446777 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_068.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_068.json new file mode 100644 index 0000000..994ee9a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_068.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 116493, "MATRIX_FILE": "as-caida_G_068", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93310, "MATRIX_DENSITY": 9.47654416740232e-05, "TIME_S": 10.441468954086304, "TIME_S_1KI": 0.08963172855095417, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 920.1793681907652, "W": 73.48637679188055, "J_1KI": 7.899009967901636, "W_1KI": 0.6308222536279481, "W_D": 54.53037679188054, "J_D": 682.8167322177884, "W_D_1KI": 0.46810002997502465, "J_D_1KI": 0.004018267449331931} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_068.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_068.output new file mode 100644 index 0000000..e34095a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_068.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93310, 93310, 93310]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93310, layout=torch.sparse_csr) +tensor([0.1803, 0.0261, 0.9309, ..., 0.6717, 0.6160, 0.7093]) +Matrix: as-caida_G_068 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93310 +Density: 9.47654416740232e-05 +Time: 10.441468954086304 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_069.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_069.json new file mode 100644 index 0000000..25d1d93 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_069.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 131466, "MATRIX_FILE": "as-caida_G_069", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92190, "MATRIX_DENSITY": 9.362797200651806e-05, "TIME_S": 11.471691131591797, "TIME_S_1KI": 0.08725975637496992, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 769.0071820735931, "W": 69.24066550382902, "J_1KI": 5.849475773763507, "W_1KI": 0.5266811609376495, "W_D": 50.18866550382902, "J_D": 557.4100703725813, "W_D_1KI": 0.3817615619538817, "J_D_1KI": 0.0029038805619238566} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_069.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_069.output new file mode 100644 index 0000000..4dba15c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_069.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 92190, 92190, 92190]), + col_indices=tensor([ 106, 329, 1040, ..., 978, 19739, 160]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92190, layout=torch.sparse_csr) +tensor([0.5003, 0.6422, 0.8710, ..., 0.8132, 0.2028, 0.2500]) +Matrix: as-caida_G_069 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92190 +Density: 9.362797200651806e-05 +Time: 11.471691131591797 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_070.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_070.json new file mode 100644 index 0000000..9676daf --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_070.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 127665, "MATRIX_FILE": "as-caida_G_070", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 78684, "MATRIX_DENSITY": 7.991130653390679e-05, "TIME_S": 12.303269386291504, "TIME_S_1KI": 0.09637151440325464, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 930.5763135051726, "W": 77.8971838277324, "J_1KI": 7.2892046645922735, "W_1KI": 0.610168674481905, "W_D": 58.976183827732406, "J_D": 704.5420262224674, "W_D_1KI": 0.461960473330454, "J_D_1KI": 0.003618536586616958} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_070.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_070.output new file mode 100644 index 0000000..86c7e65 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_070.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 78684, 78684, 78684]), + col_indices=tensor([ 106, 329, 1040, ..., 16263, 2242, 2242]), + values=tensor([1., 1., 1., ..., 3., 1., 1.]), size=(31379, 31379), + nnz=78684, layout=torch.sparse_csr) +tensor([0.5095, 0.9979, 0.1625, ..., 0.8506, 0.4151, 0.9679]) +Matrix: as-caida_G_070 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 78684 +Density: 7.991130653390679e-05 +Time: 12.303269386291504 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_071.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_071.json new file mode 100644 index 0000000..4c5ba79 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_071.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 107089, "MATRIX_FILE": "as-caida_G_071", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 96012, "MATRIX_DENSITY": 9.75095872468794e-05, "TIME_S": 10.242868661880493, "TIME_S_1KI": 0.09564818666604874, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 743.9743577766419, "W": 72.75171660806772, "J_1KI": 6.947252825002026, "W_1KI": 0.6793575120513566, "W_D": 53.988716608067726, "J_D": 552.0999728715421, "W_D_1KI": 0.504148106790312, "J_D_1KI": 0.00470774875841881} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_071.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_071.output new file mode 100644 index 0000000..c4b8499 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_071.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 96011, 96011, 96012]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=96012, layout=torch.sparse_csr) +tensor([0.2232, 0.2750, 0.6777, ..., 0.0865, 0.8019, 0.8172]) +Matrix: as-caida_G_071 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 96012 +Density: 9.75095872468794e-05 +Time: 10.242868661880493 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_072.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_072.json new file mode 100644 index 0000000..f8e88f7 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_072.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 137791, "MATRIX_FILE": "as-caida_G_072", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 96404, "MATRIX_DENSITY": 9.79077016305062e-05, "TIME_S": 12.534290552139282, "TIME_S_1KI": 0.09096595969358871, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1029.9250410842894, "W": 79.2149905022375, "J_1KI": 7.474545079753318, "W_1KI": 0.5748923405900058, "W_D": 60.0399905022375, "J_D": 780.6185330915449, "W_D_1KI": 0.43573230836729177, "J_D_1KI": 0.003162269730006254} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_072.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_072.output new file mode 100644 index 0000000..b655266 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_072.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 96403, 96403, 96404]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=96404, layout=torch.sparse_csr) +tensor([0.6902, 0.4885, 0.2304, ..., 0.1800, 0.6153, 0.8350]) +Matrix: as-caida_G_072 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 96404 +Density: 9.79077016305062e-05 +Time: 12.534290552139282 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_073.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_073.json new file mode 100644 index 0000000..a223a4d --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_073.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 147913, "MATRIX_FILE": "as-caida_G_073", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 95554, "MATRIX_DENSITY": 9.704444340070319e-05, "TIME_S": 11.440205574035645, "TIME_S_1KI": 0.07734415213020927, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1025.3845811748504, "W": 78.38669452307471, "J_1KI": 6.932349294347694, "W_1KI": 0.5299513533163055, "W_D": 59.757694523074704, "J_D": 781.6966762449739, "W_D_1KI": 0.4040056960718443, "J_D_1KI": 0.0027313738215832568} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_073.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_073.output new file mode 100644 index 0000000..db0b638 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_073.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 95553, 95553, 95554]), + col_indices=tensor([22754, 22754, 106, ..., 978, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=95554, layout=torch.sparse_csr) +tensor([0.3859, 0.8936, 0.1321, ..., 0.0797, 0.0433, 0.2011]) +Matrix: as-caida_G_073 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 95554 +Density: 9.704444340070319e-05 +Time: 11.440205574035645 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_074.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_074.json new file mode 100644 index 0000000..35809ff --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_074.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 119838, "MATRIX_FILE": "as-caida_G_074", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 97296, "MATRIX_DENSITY": 9.881361497284067e-05, "TIME_S": 12.39066219329834, "TIME_S_1KI": 0.10339510166473355, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 751.5293909931183, "W": 75.59013886780932, "J_1KI": 6.271211059873481, "W_1KI": 0.6307693625378371, "W_D": 56.63213886780931, "J_D": 563.045887617588, "W_D_1KI": 0.472572463390655, "J_D_1KI": 0.003943427488698534} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_074.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_074.output new file mode 100644 index 0000000..bcdd64b --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_074.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 97295, 97295, 97296]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=97296, layout=torch.sparse_csr) +tensor([0.9807, 0.8382, 0.9810, ..., 0.3310, 0.9554, 0.8231]) +Matrix: as-caida_G_074 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 97296 +Density: 9.881361497284067e-05 +Time: 12.39066219329834 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_075.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_075.json new file mode 100644 index 0000000..f16eaab --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_075.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 107524, "MATRIX_FILE": "as-caida_G_075", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 97492, "MATRIX_DENSITY": 9.901267216465406e-05, "TIME_S": 12.727195501327515, "TIME_S_1KI": 0.11836609037356789, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 964.8045343589782, "W": 78.29730307055848, "J_1KI": 8.972922643865353, "W_1KI": 0.7281844338990224, "W_D": 59.495303070558485, "J_D": 733.1202471151352, "W_D_1KI": 0.5533211475629486, "J_D_1KI": 0.005146024585794321} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_075.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_075.output new file mode 100644 index 0000000..330c138 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_075.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 97491, 97491, 97492]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=97492, layout=torch.sparse_csr) +tensor([0.3771, 0.3076, 0.9701, ..., 0.4306, 0.8324, 0.7552]) +Matrix: as-caida_G_075 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 97492 +Density: 9.901267216465406e-05 +Time: 12.727195501327515 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_076.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_076.json new file mode 100644 index 0000000..abac702 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_076.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 130199, "MATRIX_FILE": "as-caida_G_076", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98178, "MATRIX_DENSITY": 9.970937233600097e-05, "TIME_S": 13.595388889312744, "TIME_S_1KI": 0.10442007150064704, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1313.497613773346, "W": 80.42949588978333, "J_1KI": 10.08838480920242, "W_1KI": 0.6177428082380304, "W_D": 61.59049588978333, "J_D": 1005.8370811276437, "W_D_1KI": 0.4730489165798764, "J_D_1KI": 0.0036332761125651993} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_076.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_076.output new file mode 100644 index 0000000..e54a697 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_076.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98177, 98177, 98178]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98178, layout=torch.sparse_csr) +tensor([0.5318, 0.3710, 0.2932, ..., 0.6906, 0.6650, 0.2140]) +Matrix: as-caida_G_076 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98178 +Density: 9.970937233600097e-05 +Time: 13.595388889312744 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_077.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_077.json new file mode 100644 index 0000000..1020454 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_077.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 124699, "MATRIX_FILE": "as-caida_G_077", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98664, "MATRIX_DENSITY": 0.00010020295292386482, "TIME_S": 11.544230461120605, "TIME_S_1KI": 0.09257676854762753, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 944.6338950157166, "W": 79.8676016076561, "J_1KI": 7.575312512656209, "W_1KI": 0.6404830961567944, "W_D": 60.9776016076561, "J_D": 721.2124585676193, "W_D_1KI": 0.488998320817778, "J_D_1KI": 0.003921429368461479} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_077.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_077.output new file mode 100644 index 0000000..3330ac4 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_077.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98663, 98663, 98664]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98664, layout=torch.sparse_csr) +tensor([0.8111, 0.6200, 0.5723, ..., 0.4104, 0.4244, 0.0852]) +Matrix: as-caida_G_077 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98664 +Density: 0.00010020295292386482 +Time: 11.544230461120605 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_078.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_078.json new file mode 100644 index 0000000..7ec9cad --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_078.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 132785, "MATRIX_FILE": "as-caida_G_078", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98782, "MATRIX_DENSITY": 0.00010032279347811982, "TIME_S": 12.249173164367676, "TIME_S_1KI": 0.09224816932912358, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1212.3952165508272, "W": 81.2409798902157, "J_1KI": 9.130513360325542, "W_1KI": 0.6118234732101946, "W_D": 62.4989798902157, "J_D": 932.7000284905436, "W_D_1KI": 0.47067801250303654, "J_D_1KI": 0.00354466251837961} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_078.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_078.output new file mode 100644 index 0000000..4bc4199 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_078.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98781, 98781, 98782]), + col_indices=tensor([22754, 22754, 106, ..., 4133, 31329, 12170]), + values=tensor([1., 1., 1., ..., 3., 3., 1.]), size=(31379, 31379), + nnz=98782, layout=torch.sparse_csr) +tensor([0.4834, 0.9284, 0.2623, ..., 0.9344, 0.3302, 0.9930]) +Matrix: as-caida_G_078 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98782 +Density: 0.00010032279347811982 +Time: 12.249173164367676 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_079.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_079.json new file mode 100644 index 0000000..842ec0b --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_079.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 116178, "MATRIX_FILE": "as-caida_G_079", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98392, "MATRIX_DENSITY": 9.992671029032785e-05, "TIME_S": 10.857849597930908, "TIME_S_1KI": 0.09345874087977851, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 816.0714656066896, "W": 75.64987475745906, "J_1KI": 7.024320143286075, "W_1KI": 0.6511549067591029, "W_D": 56.60087475745906, "J_D": 610.5807705039979, "W_D_1KI": 0.48719098932206667, "J_D_1KI": 0.004193487487493903} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_079.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_079.output new file mode 100644 index 0000000..4584ea5 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_079.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 98391, 98391, 98392]), + col_indices=tensor([22754, 106, 329, ..., 4133, 31329, 12170]), + values=tensor([1., 1., 1., ..., 3., 3., 1.]), size=(31379, 31379), + nnz=98392, layout=torch.sparse_csr) +tensor([0.4019, 0.4736, 0.2605, ..., 0.3907, 0.0593, 0.9888]) +Matrix: as-caida_G_079 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98392 +Density: 9.992671029032785e-05 +Time: 10.857849597930908 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_080.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_080.json new file mode 100644 index 0000000..ae06096 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_080.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 108613, "MATRIX_FILE": "as-caida_G_080", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98112, "MATRIX_DENSITY": 9.964234287345156e-05, "TIME_S": 12.500170946121216, "TIME_S_1KI": 0.11508908644564846, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 876.7796450424196, "W": 80.656684068133, "J_1KI": 8.072511071809265, "W_1KI": 0.7426061711593732, "W_D": 61.808684068133005, "J_D": 671.8921897659303, "W_D_1KI": 0.5690726162442157, "J_D_1KI": 0.005239452148860778} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_080.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_080.output new file mode 100644 index 0000000..04b5c98 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_080.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98111, 98111, 98112]), + col_indices=tensor([22754, 22754, 106, ..., 4133, 31329, 12170]), + values=tensor([1., 1., 1., ..., 3., 3., 1.]), size=(31379, 31379), + nnz=98112, layout=torch.sparse_csr) +tensor([0.7419, 0.0158, 0.4611, ..., 0.3370, 0.3761, 0.2953]) +Matrix: as-caida_G_080 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98112 +Density: 9.964234287345156e-05 +Time: 12.500170946121216 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_081.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_081.json new file mode 100644 index 0000000..781298e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_081.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 96525, "MATRIX_FILE": "as-caida_G_081", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85988, "MATRIX_DENSITY": 8.732923372270826e-05, "TIME_S": 10.434698820114136, "TIME_S_1KI": 0.10810358787997032, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 720.3386605739594, "W": 70.13948634210955, "J_1KI": 7.4627159862622054, "W_1KI": 0.72664580515006, "W_D": 51.47748634210955, "J_D": 528.6782880120278, "W_D_1KI": 0.5333072918115467, "J_D_1KI": 0.005525069068236692} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_081.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_081.output new file mode 100644 index 0000000..95cfab7 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_081.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 85987, 85987, 85988]), + col_indices=tensor([22754, 106, 329, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=85988, layout=torch.sparse_csr) +tensor([0.6790, 0.5859, 0.9890, ..., 0.4285, 0.4926, 0.6752]) +Matrix: as-caida_G_081 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85988 +Density: 8.732923372270826e-05 +Time: 10.434698820114136 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_082.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_082.json new file mode 100644 index 0000000..01db491 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_082.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 125242, "MATRIX_FILE": "as-caida_G_082", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98400, "MATRIX_DENSITY": 9.993483507366717e-05, "TIME_S": 11.815460920333862, "TIME_S_1KI": 0.09434104310322305, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 983.8958874511718, "W": 82.174835758592, "J_1KI": 7.855957964989154, "W_1KI": 0.6561284214448188, "W_D": 63.373835758591994, "J_D": 758.7877213172911, "W_D_1KI": 0.5060110486784944, "J_D_1KI": 0.004040266433612482} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_082.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_082.output new file mode 100644 index 0000000..349e00e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_082.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 98399, 98399, 98400]), + col_indices=tensor([22754, 106, 329, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98400, layout=torch.sparse_csr) +tensor([0.5805, 0.8333, 0.0040, ..., 0.4311, 0.3744, 0.7798]) +Matrix: as-caida_G_082 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98400 +Density: 9.993483507366717e-05 +Time: 11.815460920333862 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_083.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_083.json new file mode 100644 index 0000000..e40bd6b --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_083.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 122181, "MATRIX_FILE": "as-caida_G_083", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98450, "MATRIX_DENSITY": 9.998561496953794e-05, "TIME_S": 10.756187200546265, "TIME_S_1KI": 0.08803485976171635, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 829.9369350624085, "W": 74.82598068470843, "J_1KI": 6.792684092145329, "W_1KI": 0.6124191215058677, "W_D": 55.96498068470842, "J_D": 620.7390015509128, "W_D_1KI": 0.45804978421119835, "J_D_1KI": 0.0037489444693626535} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_083.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_083.output new file mode 100644 index 0000000..9c43f27 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_083.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98449, 98449, 98450]), + col_indices=tensor([22754, 22754, 106, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98450, layout=torch.sparse_csr) +tensor([0.5323, 0.2167, 0.2218, ..., 0.0798, 0.4248, 0.4437]) +Matrix: as-caida_G_083 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98450 +Density: 9.998561496953794e-05 +Time: 10.756187200546265 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_084.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_084.json new file mode 100644 index 0000000..3aa7104 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_084.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 133691, "MATRIX_FILE": "as-caida_G_084", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 97972, "MATRIX_DENSITY": 9.950015916501341e-05, "TIME_S": 14.734516620635986, "TIME_S_1KI": 0.11021322767154099, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1164.477148323059, "W": 78.60727913174769, "J_1KI": 8.710213464803607, "W_1KI": 0.5879773442621246, "W_D": 59.77527913174769, "J_D": 885.5025559005737, "W_D_1KI": 0.4471152069454764, "J_D_1KI": 0.003344392718623366} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_084.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_084.output new file mode 100644 index 0000000..a1fff97 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_084.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 97971, 97971, 97972]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=97972, layout=torch.sparse_csr) +tensor([0.2329, 0.6136, 0.1303, ..., 0.4611, 0.0500, 0.9326]) +Matrix: as-caida_G_084 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 97972 +Density: 9.950015916501341e-05 +Time: 14.734516620635986 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_085.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_085.json new file mode 100644 index 0000000..175f606 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_085.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 132823, "MATRIX_FILE": "as-caida_G_085", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99166, "MATRIX_DENSITY": 0.0001007127830784073, "TIME_S": 15.898339748382568, "TIME_S_1KI": 0.1196956833408564, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 871.5308598327637, "W": 80.49591528124886, "J_1KI": 6.5615959572721865, "W_1KI": 0.6060389788007262, "W_D": 61.56191528124885, "J_D": 666.5320689945221, "W_D_1KI": 0.4634883663315002, "J_D_1KI": 0.0034895188810032916} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_085.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_085.output new file mode 100644 index 0000000..78dc496 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_085.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99165, 99165, 99166]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99166, layout=torch.sparse_csr) +tensor([0.9167, 0.3986, 0.2869, ..., 0.7443, 0.4462, 0.7217]) +Matrix: as-caida_G_085 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99166 +Density: 0.0001007127830784073 +Time: 15.898339748382568 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_086.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_086.json new file mode 100644 index 0000000..47ae3df --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_086.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 131644, "MATRIX_FILE": "as-caida_G_086", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99660, "MATRIX_DENSITY": 0.00010121448844961047, "TIME_S": 12.412601470947266, "TIME_S_1KI": 0.09428915462115452, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 922.9358431625367, "W": 76.58562821349105, "J_1KI": 7.010846245651429, "W_1KI": 0.5817631507208156, "W_D": 57.632628213491046, "J_D": 694.5326369278432, "W_D_1KI": 0.43779153028995654, "J_D_1KI": 0.003325571467670054} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_086.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_086.output new file mode 100644 index 0000000..bca8a30 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_086.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99659, 99659, 99660]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99660, layout=torch.sparse_csr) +tensor([0.1038, 0.0079, 0.5436, ..., 0.0943, 0.7115, 0.5985]) +Matrix: as-caida_G_086 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99660 +Density: 0.00010121448844961047 +Time: 12.412601470947266 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_087.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_087.json new file mode 100644 index 0000000..91c1b09 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_087.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 115010, "MATRIX_FILE": "as-caida_G_087", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99652, "MATRIX_DENSITY": 0.00010120636366627115, "TIME_S": 10.317447185516357, "TIME_S_1KI": 0.08970913125394625, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 594.8110333919525, "W": 65.48176967882961, "J_1KI": 5.171820132092448, "W_1KI": 0.5693571835390802, "W_D": 46.58276967882961, "J_D": 423.1398373444081, "W_D_1KI": 0.40503234222093387, "J_D_1KI": 0.003521714131127153} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_087.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_087.output new file mode 100644 index 0000000..21308f6 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_087.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99651, 99651, 99652]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99652, layout=torch.sparse_csr) +tensor([0.5990, 0.3269, 0.9590, ..., 0.9273, 0.7552, 0.7152]) +Matrix: as-caida_G_087 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99652 +Density: 0.00010120636366627115 +Time: 10.317447185516357 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_088.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_088.json new file mode 100644 index 0000000..fb7cabb --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_088.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 131756, "MATRIX_FILE": "as-caida_G_088", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 100366, "MATRIX_DENSITY": 0.00010193150057930568, "TIME_S": 13.073508977890015, "TIME_S_1KI": 0.09922515086895485, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 642.3477029418946, "W": 66.87126501636561, "J_1KI": 4.8752823624115385, "W_1KI": 0.5075386700899056, "W_D": 47.69226501636561, "J_D": 458.1192964401246, "W_D_1KI": 0.36197414171928116, "J_D_1KI": 0.0027473067011694434} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_088.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_088.output new file mode 100644 index 0000000..7107c78 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_088.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 100365, 100365, + 100366]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=100366, layout=torch.sparse_csr) +tensor([0.6682, 0.5821, 0.7332, ..., 0.5584, 0.4746, 0.6060]) +Matrix: as-caida_G_088 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 100366 +Density: 0.00010193150057930568 +Time: 13.073508977890015 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_089.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_089.json new file mode 100644 index 0000000..1182df6 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_089.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 113243, "MATRIX_FILE": "as-caida_G_089", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 101476, "MATRIX_DENSITY": 0.00010305881426763669, "TIME_S": 11.973927021026611, "TIME_S_1KI": 0.10573657551483634, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 788.3404119873047, "W": 75.75014646671524, "J_1KI": 6.961493531496911, "W_1KI": 0.6689168113412329, "W_D": 56.510146466715234, "J_D": 588.1075380706787, "W_D_1KI": 0.499016685064112, "J_D_1KI": 0.0044066007176082585} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_089.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_089.output new file mode 100644 index 0000000..be909e1 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_089.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 101475, 101475, + 101476]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=101476, layout=torch.sparse_csr) +tensor([0.8580, 0.8395, 0.8160, ..., 0.7325, 0.8470, 0.1997]) +Matrix: as-caida_G_089 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 101476 +Density: 0.00010305881426763669 +Time: 11.973927021026611 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_090.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_090.json new file mode 100644 index 0000000..bf832f9 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_090.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 80317, "MATRIX_FILE": "as-caida_G_090", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 100924, "MATRIX_DENSITY": 0.00010249820421722343, "TIME_S": 10.799185514450073, "TIME_S_1KI": 0.13445703293761063, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 400.43680762290955, "W": 54.79486752642867, "J_1KI": 4.9857042422265465, "W_1KI": 0.6822324978077949, "W_D": 35.90686752642867, "J_D": 262.40471148300173, "W_D_1KI": 0.4470643515871941, "J_D_1KI": 0.0055662481365986545} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_090.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_090.output new file mode 100644 index 0000000..17f6c02 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_090.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 100923, 100923, + 100924]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=100924, layout=torch.sparse_csr) +tensor([0.5621, 0.5240, 0.1840, ..., 0.2555, 0.8128, 0.1098]) +Matrix: as-caida_G_090 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 100924 +Density: 0.00010249820421722343 +Time: 10.799185514450073 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_091.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_091.json new file mode 100644 index 0000000..eb1d0ed --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_091.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 129251, "MATRIX_FILE": "as-caida_G_091", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 101654, "MATRIX_DENSITY": 0.00010323959069693661, "TIME_S": 11.867344617843628, "TIME_S_1KI": 0.09181626925782878, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 885.472681055069, "W": 76.52432049837114, "J_1KI": 6.850799460391556, "W_1KI": 0.5920597944957574, "W_D": 57.47432049837114, "J_D": 665.042699263096, "W_D_1KI": 0.44467215339433463, "J_D_1KI": 0.0034403768898835186} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_091.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_091.output new file mode 100644 index 0000000..20939ae --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_091.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 101653, 101653, + 101654]), + col_indices=tensor([ 106, 329, 1040, ..., 19739, 155, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=101654, layout=torch.sparse_csr) +tensor([0.2912, 0.5789, 0.6574, ..., 0.8896, 0.8910, 0.3263]) +Matrix: as-caida_G_091 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 101654 +Density: 0.00010323959069693661 +Time: 11.867344617843628 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_092.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_092.json new file mode 100644 index 0000000..3fd3102 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_092.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 126507, "MATRIX_FILE": "as-caida_G_092", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 101762, "MATRIX_DENSITY": 0.00010334927527201746, "TIME_S": 12.881949424743652, "TIME_S_1KI": 0.10182795754182498, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 763.0945223999023, "W": 79.26782134959922, "J_1KI": 6.032033977565686, "W_1KI": 0.626588420795681, "W_D": 60.25182134959922, "J_D": 580.0315191421508, "W_D_1KI": 0.4762726279937017, "J_D_1KI": 0.0037647926833590368} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_092.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_092.output new file mode 100644 index 0000000..32cafae --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_092.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 101761, 101761, + 101762]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=101762, layout=torch.sparse_csr) +tensor([0.3569, 0.6237, 0.2710, ..., 0.0016, 0.7867, 0.0147]) +Matrix: as-caida_G_092 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 101762 +Density: 0.00010334927527201746 +Time: 12.881949424743652 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_093.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_093.json new file mode 100644 index 0000000..90f7b63 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_093.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 99968, "MATRIX_FILE": "as-caida_G_093", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99916, "MATRIX_DENSITY": 0.0001014744815164688, "TIME_S": 10.715639352798462, "TIME_S_1KI": 0.10719069455024069, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 494.5545548248291, "W": 60.45623386944561, "J_1KI": 4.947128629409701, "W_1KI": 0.6047558605698384, "W_D": 41.78923386944561, "J_D": 341.85152845287325, "W_D_1KI": 0.4180261070487117, "J_D_1KI": 0.0041815991822254294} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_093.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_093.output new file mode 100644 index 0000000..00bfd93 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_093.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99914, 99915, 99916]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99916, layout=torch.sparse_csr) +tensor([0.6294, 0.8502, 0.3298, ..., 0.4895, 0.7009, 0.0682]) +Matrix: as-caida_G_093 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99916 +Density: 0.0001014744815164688 +Time: 10.715639352798462 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_094.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_094.json new file mode 100644 index 0000000..f6878d3 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_094.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 128480, "MATRIX_FILE": "as-caida_G_094", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102476, "MATRIX_DENSITY": 0.000104074412185052, "TIME_S": 14.379862546920776, "TIME_S_1KI": 0.11192296502895997, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 732.5010242176056, "W": 73.36879417111618, "J_1KI": 5.701284435068537, "W_1KI": 0.5710522584924983, "W_D": 54.60879417111617, "J_D": 545.2045125389099, "W_D_1KI": 0.42503731453234883, "J_D_1KI": 0.0033081982762480453} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_094.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_094.output new file mode 100644 index 0000000..f634386 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_094.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102474, 102475, + 102476]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102476, layout=torch.sparse_csr) +tensor([0.9047, 0.7349, 0.8055, ..., 0.2998, 0.4731, 0.0554]) +Matrix: as-caida_G_094 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102476 +Density: 0.000104074412185052 +Time: 14.379862546920776 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_095.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_095.json new file mode 100644 index 0000000..324332e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_095.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 117979, "MATRIX_FILE": "as-caida_G_095", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102290, "MATRIX_DENSITY": 0.00010388551097241275, "TIME_S": 10.821407318115234, "TIME_S_1KI": 0.091723165293105, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1032.7791000175475, "W": 76.62148067876558, "J_1KI": 8.7539231559646, "W_1KI": 0.6494501621370378, "W_D": 57.65148067876558, "J_D": 777.0829250836372, "W_D_1KI": 0.48865883486693035, "J_D_1KI": 0.004141913686901316} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_095.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_095.output new file mode 100644 index 0000000..a1a9b7f --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_095.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102289, 102289, + 102290]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 25970, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102290, layout=torch.sparse_csr) +tensor([0.0878, 0.3668, 0.1096, ..., 0.2472, 0.7774, 0.5495]) +Matrix: as-caida_G_095 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102290 +Density: 0.00010388551097241275 +Time: 10.821407318115234 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_096.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_096.json new file mode 100644 index 0000000..4d2969f --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_096.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 133246, "MATRIX_FILE": "as-caida_G_096", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102356, "MATRIX_DENSITY": 0.00010395254043496216, "TIME_S": 11.407078742980957, "TIME_S_1KI": 0.08560916457515391, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 909.9383479404449, "W": 74.88878066809822, "J_1KI": 6.829010611503872, "W_1KI": 0.5620339872724001, "W_D": 55.95578066809822, "J_D": 679.8923705875873, "W_D_1KI": 0.4199434179494936, "J_D_1KI": 0.003151639958794212} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_096.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_096.output new file mode 100644 index 0000000..209ed82 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_096.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102354, 102355, + 102356]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102356, layout=torch.sparse_csr) +tensor([0.6937, 0.1321, 0.3726, ..., 0.4796, 0.6582, 0.4170]) +Matrix: as-caida_G_096 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102356 +Density: 0.00010395254043496216 +Time: 11.407078742980957 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_097.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_097.json new file mode 100644 index 0000000..9f1b027 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_097.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 122941, "MATRIX_FILE": "as-caida_G_097", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102212, "MATRIX_DENSITY": 0.00010380629433485436, "TIME_S": 12.524338960647583, "TIME_S_1KI": 0.10187275978434845, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 843.8680956840516, "W": 74.14214847163694, "J_1KI": 6.864008717059821, "W_1KI": 0.6030709728376777, "W_D": 55.321148471636945, "J_D": 629.6520019199849, "W_D_1KI": 0.4499812794074958, "J_D_1KI": 0.0036601400623672803} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_097.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_097.output new file mode 100644 index 0000000..bffa648 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_097.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102210, 102211, + 102212]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102212, layout=torch.sparse_csr) +tensor([0.0633, 0.9741, 0.0341, ..., 0.1367, 0.8315, 0.0249]) +Matrix: as-caida_G_097 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102212 +Density: 0.00010380629433485436 +Time: 12.524338960647583 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_098.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_098.json new file mode 100644 index 0000000..5821d8f --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_098.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 126756, "MATRIX_FILE": "as-caida_G_098", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102468, "MATRIX_DENSITY": 0.00010406628740171267, "TIME_S": 11.859320640563965, "TIME_S_1KI": 0.09356023099943171, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1051.9725153255463, "W": 81.7830300475806, "J_1KI": 8.299193058518304, "W_1KI": 0.645200464258738, "W_D": 62.83003004758059, "J_D": 808.1806789095402, "W_D_1KI": 0.49567697030184443, "J_D_1KI": 0.003910481320819878} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_098.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_098.output new file mode 100644 index 0000000..b25541c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_098.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102466, 102467, + 102468]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102468, layout=torch.sparse_csr) +tensor([0.5946, 0.0797, 0.7280, ..., 0.9345, 0.4625, 0.8121]) +Matrix: as-caida_G_098 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102468 +Density: 0.00010406628740171267 +Time: 11.859320640563965 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_099.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_099.json new file mode 100644 index 0000000..0c76966 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_099.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 121330, "MATRIX_FILE": "as-caida_G_099", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 103510, "MATRIX_DENSITY": 0.00010512454043165944, "TIME_S": 12.897506713867188, "TIME_S_1KI": 0.1063010526157355, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 697.9706234169006, "W": 68.31345187395345, "J_1KI": 5.752663178248583, "W_1KI": 0.5630384230936574, "W_D": 49.40545187395345, "J_D": 504.7842423229218, "W_D_1KI": 0.4071989769550272, "J_D_1KI": 0.0033561277256657644} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_099.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_099.output new file mode 100644 index 0000000..30e9589 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_099.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 103508, 103509, + 103510]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=103510, layout=torch.sparse_csr) +tensor([0.4721, 0.5288, 0.3501, ..., 0.8329, 0.8712, 0.4048]) +Matrix: as-caida_G_099 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 103510 +Density: 0.00010512454043165944 +Time: 12.897506713867188 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_100.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_100.json new file mode 100644 index 0000000..b0ec62a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_100.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 142071, "MATRIX_FILE": "as-caida_G_100", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102888, "MATRIX_DENSITY": 0.00010449283852702711, "TIME_S": 14.072954654693604, "TIME_S_1KI": 0.09905578657638507, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 943.3167991638184, "W": 76.39082030637593, "J_1KI": 6.639756172363244, "W_1KI": 0.5376946759463643, "W_D": 57.404820306375925, "J_D": 708.8669964637755, "W_D_1KI": 0.404057269297576, "J_D_1KI": 0.0028440517015969197} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_100.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_100.output new file mode 100644 index 0000000..4dba7d2 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_100.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102886, 102887, + 102888]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102888, layout=torch.sparse_csr) +tensor([0.4732, 0.6141, 0.3248, ..., 0.5854, 0.3585, 0.4654]) +Matrix: as-caida_G_100 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102888 +Density: 0.00010449283852702711 +Time: 14.072954654693604 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_101.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_101.json new file mode 100644 index 0000000..98c89ca --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_101.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 115969, "MATRIX_FILE": "as-caida_G_101", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 103020, "MATRIX_DENSITY": 0.00010462689745212593, "TIME_S": 10.052980422973633, "TIME_S_1KI": 0.08668679063347647, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1011.7929986381531, "W": 79.35934835746973, "J_1KI": 8.724685033398176, "W_1KI": 0.6843151907619254, "W_D": 60.604348357469725, "J_D": 772.6758929383755, "W_D_1KI": 0.5225909368664878, "J_D_1KI": 0.004506298552772619} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_101.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_101.output new file mode 100644 index 0000000..046a855 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_101.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 103017, 103018, + 103020]), + col_indices=tensor([ 106, 329, 1040, ..., 5128, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=103020, layout=torch.sparse_csr) +tensor([0.2677, 0.7279, 0.8125, ..., 0.2256, 0.4274, 0.1891]) +Matrix: as-caida_G_101 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 103020 +Density: 0.00010462689745212593 +Time: 10.052980422973633 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_102.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_102.json new file mode 100644 index 0000000..61ef112 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_102.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 142560, "MATRIX_FILE": "as-caida_G_102", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104096, "MATRIX_DENSITY": 0.00010571968081126482, "TIME_S": 15.321743965148926, "TIME_S_1KI": 0.10747575733129155, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 960.3875262641906, "W": 80.9739076785938, "J_1KI": 6.736725071999092, "W_1KI": 0.5679987912359273, "W_D": 62.043907678593804, "J_D": 735.8690808367728, "W_D_1KI": 0.4352125959497321, "J_D_1KI": 0.0030528380748438} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_102.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_102.output new file mode 100644 index 0000000..00939c8 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_102.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104094, 104094, + 104096]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104096, layout=torch.sparse_csr) +tensor([0.8026, 0.0282, 0.6140, ..., 0.3912, 0.3347, 0.4761]) +Matrix: as-caida_G_102 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104096 +Density: 0.00010571968081126482 +Time: 15.321743965148926 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_103.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_103.json new file mode 100644 index 0000000..17f5bc0 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_103.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 100361, "MATRIX_FILE": "as-caida_G_103", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104634, "MATRIX_DENSITY": 0.00010626607249083426, "TIME_S": 11.295690774917603, "TIME_S_1KI": 0.11255060008287683, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 772.0949514770507, "W": 77.67538217492972, "J_1KI": 7.69317714527606, "W_1KI": 0.7739598267746408, "W_D": 58.84638217492972, "J_D": 584.9342908623217, "W_D_1KI": 0.5863471086869374, "J_D_1KI": 0.0058423800947274085} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_103.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_103.output new file mode 100644 index 0000000..ff6e0eb --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_103.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104632, 104632, + 104634]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104634, layout=torch.sparse_csr) +tensor([0.1121, 0.4709, 0.9595, ..., 0.9605, 0.6235, 0.1098]) +Matrix: as-caida_G_103 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104634 +Density: 0.00010626607249083426 +Time: 11.295690774917603 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_104.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_104.json new file mode 100644 index 0000000..fc10b9d --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_104.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 139098, "MATRIX_FILE": "as-caida_G_104", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104824, "MATRIX_DENSITY": 0.00010645903609514317, "TIME_S": 12.943524837493896, "TIME_S_1KI": 0.09305327781487797, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 945.8908369159699, "W": 75.44521536642654, "J_1KI": 6.800175681289233, "W_1KI": 0.5423889298654656, "W_D": 56.21721536642654, "J_D": 704.8206918592454, "W_D_1KI": 0.40415545418644794, "J_D_1KI": 0.0029055446820691016} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_104.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_104.output new file mode 100644 index 0000000..db7ba51 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_104.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104823, 104823, + 104824]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104824, layout=torch.sparse_csr) +tensor([0.0345, 0.7174, 0.6810, ..., 0.9568, 0.1585, 0.9648]) +Matrix: as-caida_G_104 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104824 +Density: 0.00010645903609514317 +Time: 12.943524837493896 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_105.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_105.json new file mode 100644 index 0000000..6b72ff2 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_105.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 110682, "MATRIX_FILE": "as-caida_G_105", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104726, "MATRIX_DENSITY": 0.00010635950749923647, "TIME_S": 10.269282817840576, "TIME_S_1KI": 0.09278186893840532, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 661.198120727539, "W": 72.53129354755693, "J_1KI": 5.973854111125016, "W_1KI": 0.6553124586432928, "W_D": 53.68529354755693, "J_D": 489.39724452972416, "W_D_1KI": 0.48504086976705274, "J_D_1KI": 0.004382292240536426} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_105.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_105.output new file mode 100644 index 0000000..8d808af --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_105.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104725, 104725, + 104726]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104726, layout=torch.sparse_csr) +tensor([0.8434, 0.8923, 0.8229, ..., 0.2622, 0.5153, 0.5666]) +Matrix: as-caida_G_105 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104726 +Density: 0.00010635950749923647 +Time: 10.269282817840576 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_106.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_106.json new file mode 100644 index 0000000..acec614 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_106.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 118611, "MATRIX_FILE": "as-caida_G_106", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105092, "MATRIX_DENSITY": 0.00010673121633701047, "TIME_S": 10.551599979400635, "TIME_S_1KI": 0.08895970845369008, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 731.3247955322266, "W": 68.49536583541321, "J_1KI": 6.165741756938451, "W_1KI": 0.5774790351267016, "W_D": 49.609365835413215, "J_D": 529.6790357065203, "W_D_1KI": 0.41825265646030485, "J_D_1KI": 0.0035262552078669336} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_106.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_106.output new file mode 100644 index 0000000..f5fb12a --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_106.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105091, 105091, + 105092]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105092, layout=torch.sparse_csr) +tensor([0.2524, 0.2221, 0.0659, ..., 0.8389, 0.9934, 0.7064]) +Matrix: as-caida_G_106 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105092 +Density: 0.00010673121633701047 +Time: 10.551599979400635 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_107.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_107.json new file mode 100644 index 0000000..6b4172d --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_107.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 102828, "MATRIX_FILE": "as-caida_G_107", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105332, "MATRIX_DENSITY": 0.00010697495983719015, "TIME_S": 10.308605194091797, "TIME_S_1KI": 0.10025095493534637, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 855.3094169616699, "W": 80.29084490007342, "J_1KI": 8.317864948862857, "W_1KI": 0.7808266707518714, "W_D": 61.65084490007342, "J_D": 656.74421875, "W_D_1KI": 0.5995530876811124, "J_D_1KI": 0.005830640367225973} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_107.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_107.output new file mode 100644 index 0000000..125707b --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_107.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105330, 105330, + 105332]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105332, layout=torch.sparse_csr) +tensor([0.6778, 0.1668, 0.3933, ..., 0.3614, 0.5997, 0.0596]) +Matrix: as-caida_G_107 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105332 +Density: 0.00010697495983719015 +Time: 10.308605194091797 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_108.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_108.json new file mode 100644 index 0000000..8fc686f --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_108.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 106749, "MATRIX_FILE": "as-caida_G_108", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105524, "MATRIX_DENSITY": 0.0001071699546373339, "TIME_S": 10.985159397125244, "TIME_S_1KI": 0.1029064384408776, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 623.6469565296172, "W": 66.44934367018328, "J_1KI": 5.8421807841723785, "W_1KI": 0.6224821185227336, "W_D": 47.70734367018328, "J_D": 447.7476832833289, "W_D_1KI": 0.4469113871809879, "J_D_1KI": 0.004186562751697795} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_108.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_108.output new file mode 100644 index 0000000..36483c6 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_108.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105522, 105522, + 105524]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105524, layout=torch.sparse_csr) +tensor([0.0413, 0.8662, 0.9707, ..., 0.2841, 0.5452, 0.2422]) +Matrix: as-caida_G_108 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105524 +Density: 0.0001071699546373339 +Time: 10.985159397125244 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_109.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_109.json new file mode 100644 index 0000000..4bd2a82 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_109.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 108141, "MATRIX_FILE": "as-caida_G_109", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104802, "MATRIX_DENSITY": 0.00010643669294096003, "TIME_S": 10.650083541870117, "TIME_S_1KI": 0.09848330921546979, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 861.2348067760468, "W": 79.56934816641592, "J_1KI": 7.9639989160082365, "W_1KI": 0.7357926056390817, "W_D": 61.17334816641592, "J_D": 662.1220093164444, "W_D_1KI": 0.5656813619849633, "J_D_1KI": 0.005230961078452791} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_109.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_109.output new file mode 100644 index 0000000..901d5c7 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_109.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104801, 104801, + 104802]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104802, layout=torch.sparse_csr) +tensor([0.0459, 0.8330, 0.8154, ..., 0.6883, 0.4090, 0.0892]) +Matrix: as-caida_G_109 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104802 +Density: 0.00010643669294096003 +Time: 10.650083541870117 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_110.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_110.json new file mode 100644 index 0000000..96aa245 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_110.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 102710, "MATRIX_FILE": "as-caida_G_110", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104846, "MATRIX_DENSITY": 0.0001064813792493263, "TIME_S": 10.078580141067505, "TIME_S_1KI": 0.09812657132769453, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 641.6866761493683, "W": 67.23597523402496, "J_1KI": 6.247557941284863, "W_1KI": 0.6546195622045075, "W_D": 48.49797523402496, "J_D": 462.8549585185051, "W_D_1KI": 0.47218357739290195, "J_D_1KI": 0.004597250291041787} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_110.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_110.output new file mode 100644 index 0000000..0e69e66 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_110.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104844, 104844, + 104846]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104846, layout=torch.sparse_csr) +tensor([0.8469, 0.3386, 0.4781, ..., 0.8726, 0.6247, 0.3641]) +Matrix: as-caida_G_110 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104846 +Density: 0.0001064813792493263 +Time: 10.078580141067505 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_111.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_111.json new file mode 100644 index 0000000..75f22e7 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_111.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 129608, "MATRIX_FILE": "as-caida_G_111", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104766, "MATRIX_DENSITY": 0.00010640013141593308, "TIME_S": 10.07983136177063, "TIME_S_1KI": 0.07777167583614153, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1008.3367251586915, "W": 80.41118685625736, "J_1KI": 7.779895725253777, "W_1KI": 0.6204183912741293, "W_D": 61.47218685625736, "J_D": 770.846271598816, "W_D_1KI": 0.47429315209136286, "J_D_1KI": 0.003659443491847439} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_111.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_111.output new file mode 100644 index 0000000..83edebd --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_111.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104764, 104764, + 104766]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104766, layout=torch.sparse_csr) +tensor([0.7452, 0.6276, 0.3285, ..., 0.0217, 0.9158, 0.2853]) +Matrix: as-caida_G_111 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104766 +Density: 0.00010640013141593308 +Time: 10.07983136177063 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_112.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_112.json new file mode 100644 index 0000000..bbdfff9 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_112.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 132633, "MATRIX_FILE": "as-caida_G_112", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104730, "MATRIX_DENSITY": 0.00010636356989090612, "TIME_S": 12.338322401046753, "TIME_S_1KI": 0.09302603726860399, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 692.2339403152465, "W": 72.3795450625952, "J_1KI": 5.219168233510865, "W_1KI": 0.5457129452142016, "W_D": 53.4365450625952, "J_D": 511.0641426873206, "W_D_1KI": 0.4028902691079535, "J_D_1KI": 0.003037632181342151} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_112.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_112.output new file mode 100644 index 0000000..da992a7 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_112.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104728, 104728, + 104730]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104730, layout=torch.sparse_csr) +tensor([0.1705, 0.3988, 0.6756, ..., 0.2087, 0.4797, 0.8746]) +Matrix: as-caida_G_112 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104730 +Density: 0.00010636356989090612 +Time: 12.338322401046753 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_113.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_113.json new file mode 100644 index 0000000..9a9d05e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_113.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 114169, "MATRIX_FILE": "as-caida_G_113", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105382, "MATRIX_DENSITY": 0.00010702573973306091, "TIME_S": 11.831740617752075, "TIME_S_1KI": 0.10363356618479688, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 760.0762902832031, "W": 77.54706898108508, "J_1KI": 6.657466477618295, "W_1KI": 0.6792305177507474, "W_D": 58.934068981085076, "J_D": 577.6412843322754, "W_D_1KI": 0.5162002731134115, "J_D_1KI": 0.004521369838690113} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_113.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_113.output new file mode 100644 index 0000000..06e33d5 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_113.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105381, 105381, + 105382]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105382, layout=torch.sparse_csr) +tensor([0.9669, 0.0581, 0.9930, ..., 0.5736, 0.0075, 0.1133]) +Matrix: as-caida_G_113 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105382 +Density: 0.00010702573973306091 +Time: 11.831740617752075 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_114.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_114.json new file mode 100644 index 0000000..628e1d2 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_114.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 110757, "MATRIX_FILE": "as-caida_G_114", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 36406, "MATRIX_DENSITY": 3.6973857781422023e-05, "TIME_S": 10.006366729736328, "TIME_S_1KI": 0.0903452308182447, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 480.56348777770995, "W": 59.21271151843787, "J_1KI": 4.338899462586653, "W_1KI": 0.5346182319712331, "W_D": 40.51471151843787, "J_D": 328.8126919765472, "W_D_1KI": 0.3657982025374276, "J_D_1KI": 0.0033027095581988283} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_114.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_114.output new file mode 100644 index 0000000..85d08a2 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_114.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 36405, 36405, 36406]), + col_indices=tensor([ 106, 329, 1040, ..., 1683, 1683, 12170]), + values=tensor([1., 1., 1., ..., 2., 2., 1.]), size=(31379, 31379), + nnz=36406, layout=torch.sparse_csr) +tensor([0.3697, 0.5772, 0.3092, ..., 0.0126, 0.4892, 0.8898]) +Matrix: as-caida_G_114 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 36406 +Density: 3.6973857781422023e-05 +Time: 10.006366729736328 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_115.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_115.json new file mode 100644 index 0000000..c716e0f --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_115.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 127219, "MATRIX_FILE": "as-caida_G_115", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106312, "MATRIX_DENSITY": 0.00010797024579625715, "TIME_S": 11.976754903793335, "TIME_S_1KI": 0.09414281596139991, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1167.8325610446932, "W": 81.07558490587088, "J_1KI": 9.179702411154727, "W_1KI": 0.6372914808784135, "W_D": 62.135584905870886, "J_D": 895.0161671590807, "W_D_1KI": 0.48841434774578396, "J_D_1KI": 0.003839161978523522} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_115.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_115.output new file mode 100644 index 0000000..c6767fb --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_115.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106311, 106311, + 106312]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106312, layout=torch.sparse_csr) +tensor([0.3085, 0.7753, 0.4233, ..., 0.7868, 0.8260, 0.3816]) +Matrix: as-caida_G_115 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106312 +Density: 0.00010797024579625715 +Time: 11.976754903793335 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_116.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_116.json new file mode 100644 index 0000000..719d3a0 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_116.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 130674, "MATRIX_FILE": "as-caida_G_116", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106578, "MATRIX_DENSITY": 0.00010824039484228964, "TIME_S": 11.13639497756958, "TIME_S_1KI": 0.08522272967514256, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1021.5756303405763, "W": 76.49837363496212, "J_1KI": 7.8177420936114, "W_1KI": 0.5854138821415287, "W_D": 57.62437363496212, "J_D": 769.5282006912232, "W_D_1KI": 0.4409781106797229, "J_D_1KI": 0.003374643086457313} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_116.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_116.output new file mode 100644 index 0000000..6ab707d --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_116.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106577, 106577, + 106578]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106578, layout=torch.sparse_csr) +tensor([0.8069, 0.2962, 0.1441, ..., 0.6054, 0.6823, 0.9809]) +Matrix: as-caida_G_116 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106578 +Density: 0.00010824039484228964 +Time: 11.13639497756958 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_117.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_117.json new file mode 100644 index 0000000..5e94f40 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_117.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 117424, "MATRIX_FILE": "as-caida_G_117", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106348, "MATRIX_DENSITY": 0.0001080068073212841, "TIME_S": 12.553772211074829, "TIME_S_1KI": 0.10690976470802245, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 743.7217671394347, "W": 70.79588167687228, "J_1KI": 6.333643608967798, "W_1KI": 0.6029081080262322, "W_D": 52.096881676872286, "J_D": 547.2858588020802, "W_D_1KI": 0.44366468249141816, "J_D_1KI": 0.0037783134835418495} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_117.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_117.output new file mode 100644 index 0000000..ced000c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_117.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106347, 106347, + 106348]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106348, layout=torch.sparse_csr) +tensor([0.5100, 0.1750, 0.8108, ..., 0.8274, 0.4963, 0.6893]) +Matrix: as-caida_G_117 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106348 +Density: 0.0001080068073212841 +Time: 12.553772211074829 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_118.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_118.json new file mode 100644 index 0000000..1de358e --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_118.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 111793, "MATRIX_FILE": "as-caida_G_118", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 107202, "MATRIX_DENSITY": 0.00010887412794275679, "TIME_S": 12.55496096611023, "TIME_S_1KI": 0.11230543026942859, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 681.1714069366454, "W": 70.5014012432552, "J_1KI": 6.09314900697401, "W_1KI": 0.630642359031918, "W_D": 51.3784012432552, "J_D": 496.40854286384575, "W_D_1KI": 0.45958513720228633, "J_D_1KI": 0.004111036801966906} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_118.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_118.output new file mode 100644 index 0000000..46c9f94 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_118.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 107201, 107201, + 107202]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=107202, layout=torch.sparse_csr) +tensor([0.3134, 0.6600, 0.1669, ..., 0.8927, 0.2213, 0.7711]) +Matrix: as-caida_G_118 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 107202 +Density: 0.00010887412794275679 +Time: 12.55496096611023 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_119.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_119.json new file mode 100644 index 0000000..cbb219c --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_119.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 119183, "MATRIX_FILE": "as-caida_G_119", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106462, "MATRIX_DENSITY": 0.00010812258548386945, "TIME_S": 11.69555115699768, "TIME_S_1KI": 0.09813103510565836, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 920.661156768799, "W": 74.54816497393028, "J_1KI": 7.7247691094266715, "W_1KI": 0.6254932748288791, "W_D": 55.75916497393028, "J_D": 688.6191946282388, "W_D_1KI": 0.46784495250103025, "J_D_1KI": 0.003925433597921098} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_119.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_119.output new file mode 100644 index 0000000..9fb3e7b --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_119.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106461, 106461, + 106462]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106462, layout=torch.sparse_csr) +tensor([0.6468, 0.5086, 0.6782, ..., 0.9558, 0.2350, 0.6466]) +Matrix: as-caida_G_119 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106462 +Density: 0.00010812258548386945 +Time: 11.69555115699768 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_120.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_120.json new file mode 100644 index 0000000..863af10 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_120.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 125835, "MATRIX_FILE": "as-caida_G_120", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106510, "MATRIX_DENSITY": 0.0001081713341839054, "TIME_S": 10.95285964012146, "TIME_S_1KI": 0.08704144029976922, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1062.0965631103513, "W": 77.76484470914684, "J_1KI": 8.440390695039943, "W_1KI": 0.6179905805948015, "W_D": 58.854844709146846, "J_D": 803.8275974416731, "W_D_1KI": 0.46771442531209, "J_D_1KI": 0.003716886600008662} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_120.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_120.output new file mode 100644 index 0000000..8b52928 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_120.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106509, 106509, + 106510]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106510, layout=torch.sparse_csr) +tensor([0.2766, 0.7155, 0.5980, ..., 0.8103, 0.7553, 0.4213]) +Matrix: as-caida_G_120 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106510 +Density: 0.0001081713341839054 +Time: 10.95285964012146 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_121.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_121.json new file mode 100644 index 0000000..54394ae --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_121.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 127448, "MATRIX_FILE": "as-caida_G_121", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106762, "MATRIX_DENSITY": 0.00010842726485909405, "TIME_S": 11.36364459991455, "TIME_S_1KI": 0.08916298882614518, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 815.087567882538, "W": 72.48275844031444, "J_1KI": 6.395452010879245, "W_1KI": 0.5687241733123661, "W_D": 53.66575844031444, "J_D": 603.4854835402967, "W_D_1KI": 0.42107964377875245, "J_D_1KI": 0.0033039329277725223} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_121.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_121.output new file mode 100644 index 0000000..b38a209 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_121.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106761, 106761, + 106762]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106762, layout=torch.sparse_csr) +tensor([0.9943, 0.5033, 0.7506, ..., 0.6989, 0.1402, 0.7789]) +Matrix: as-caida_G_121 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106762 +Density: 0.00010842726485909405 +Time: 11.36364459991455 seconds + diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_122.json b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_122.json new file mode 100644 index 0000000..5851b12 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_122.json @@ -0,0 +1 @@ +{"CPU": "ALTRA", "ITERATIONS": 104079, "MATRIX_FILE": "as-caida_G_122", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105722, "MATRIX_DENSITY": 0.00010737104302498212, "TIME_S": 11.61408257484436, "TIME_S_1KI": 0.1115891061102082, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 843.5848871135711, "W": 79.80583493379123, "J_1KI": 8.105236283146178, "W_1KI": 0.7667813385389102, "W_D": 60.96983493379123, "J_D": 644.4795842638015, "W_D_1KI": 0.5858034275290043, "J_D_1KI": 0.005628449807636548} diff --git a/pytorch/output_as-caida/altra_10_10_10_as-caida_G_122.output b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_122.output new file mode 100644 index 0000000..25479a6 --- /dev/null +++ b/pytorch/output_as-caida/altra_10_10_10_as-caida_G_122.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /space/jenkins/workspace/Releases/pytorch-dls/pytorch-dls/aten/src/ATen/SparseCsrTensorImpl.cpp:55.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105721, 105721, + 105722]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105722, layout=torch.sparse_csr) +tensor([0.2829, 0.2098, 0.7710, ..., 0.6200, 0.9270, 0.1176]) +Matrix: as-caida_G_122 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105722 +Density: 0.00010737104302498212 +Time: 11.61408257484436 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida.json new file mode 100644 index 0000000..b7b382c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 165109, "MATRIX_FILE": "as-caida", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106762, "MATRIX_DENSITY": 0.00010842726485909405, "TIME_S": 10.87175440788269, "TIME_S_1KI": 0.06584592243840548, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1170.1292817831038, "W": 105.1, "J_1KI": 7.087010894518795, "W_1KI": 0.6365491887177561, "W_D": 69.89975, "J_D": 778.2278236376643, "W_D_1KI": 0.4233551774888104, "J_D_1KI": 0.002564095097716117} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida.output new file mode 100644 index 0000000..13a12c5 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106761, 106761, + 106762]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106762, layout=torch.sparse_csr) +tensor([0.5198, 0.5159, 0.0481, ..., 0.0153, 0.5312, 0.3061]) +Matrix: as-caida +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106762 +Density: 0.00010842726485909405 +Time: 10.87175440788269 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_001.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_001.json new file mode 100644 index 0000000..b6c3556 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_001.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 183077, "MATRIX_FILE": "as-caida_G_001", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 65910, "MATRIX_DENSITY": 6.693805873684353e-05, "TIME_S": 10.614334106445312, "TIME_S_1KI": 0.05797743084300766, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1107.6763658237458, "W": 102.84, "J_1KI": 6.050330548478213, "W_1KI": 0.5617308564156066, "W_D": 66.88075, "J_D": 720.3639255500436, "W_D_1KI": 0.36531486751476155, "J_D_1KI": 0.001995416505157729} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_001.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_001.output new file mode 100644 index 0000000..9ed5722 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_001.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 148, 148, ..., 65909, 65909, 65910]), + col_indices=tensor([ 51, 111, 117, ..., 978, 8230, 12170]), + values=tensor([3., 4., 3., ..., 2., 1., 1.]), size=(31379, 31379), + nnz=65910, layout=torch.sparse_csr) +tensor([0.8380, 0.9555, 0.0255, ..., 0.7652, 0.7405, 0.3312]) +Matrix: as-caida_G_001 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 65910 +Density: 6.693805873684353e-05 +Time: 10.614334106445312 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_002.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_002.json new file mode 100644 index 0000000..e410a12 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_002.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 179542, "MATRIX_FILE": "as-caida_G_002", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 66744, "MATRIX_DENSITY": 6.77850673999679e-05, "TIME_S": 10.838684797286987, "TIME_S_1KI": 0.06036851988552532, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1067.69984978199, "W": 102.36999999999999, "J_1KI": 5.946797127034287, "W_1KI": 0.5701729957335888, "W_D": 66.74824999999998, "J_D": 696.1716957918404, "W_D_1KI": 0.37176955809782664, "J_D_1KI": 0.002070655100744264} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_002.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_002.output new file mode 100644 index 0000000..5e96e35 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_002.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 129, 129, ..., 66743, 66743, 66744]), + col_indices=tensor([ 51, 111, 117, ..., 978, 8230, 12170]), + values=tensor([3., 4., 3., ..., 2., 1., 1.]), size=(31379, 31379), + nnz=66744, layout=torch.sparse_csr) +tensor([0.0131, 0.4521, 0.5062, ..., 0.1368, 0.7099, 0.6628]) +Matrix: as-caida_G_002 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 66744 +Density: 6.77850673999679e-05 +Time: 10.838684797286987 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_003.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_003.json new file mode 100644 index 0000000..4c94b69 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_003.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 187664, "MATRIX_FILE": "as-caida_G_003", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 66680, "MATRIX_DENSITY": 6.772006913325332e-05, "TIME_S": 11.120672225952148, "TIME_S_1KI": 0.059258420506608345, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1084.8801481723785, "W": 102.5, "J_1KI": 5.7809710342547245, "W_1KI": 0.5461889334129081, "W_D": 67.1885, "J_D": 711.1362910778523, "W_D_1KI": 0.35802551368403107, "J_D_1KI": 0.0019078007166213606} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_003.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_003.output new file mode 100644 index 0000000..961b389 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_003.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 89, 89, ..., 66679, 66679, 66680]), + col_indices=tensor([ 51, 111, 117, ..., 978, 978, 12170]), + values=tensor([3., 4., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=66680, layout=torch.sparse_csr) +tensor([0.9350, 0.4181, 0.5525, ..., 0.1296, 0.9322, 0.2322]) +Matrix: as-caida_G_003 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 66680 +Density: 6.772006913325332e-05 +Time: 11.120672225952148 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_004.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_004.json new file mode 100644 index 0000000..152420e --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_004.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 185169, "MATRIX_FILE": "as-caida_G_004", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 68670, "MATRIX_DENSITY": 6.97411089889098e-05, "TIME_S": 10.784255027770996, "TIME_S_1KI": 0.05824006733184819, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1161.266316318512, "W": 102.42, "J_1KI": 6.2713862272762295, "W_1KI": 0.553116342368323, "W_D": 67.22075000000001, "J_D": 762.1674744451047, "W_D_1KI": 0.3630237782782216, "J_D_1KI": 0.00196049975038058} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_004.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_004.output new file mode 100644 index 0000000..88fef6a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_004.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 62, 62, ..., 68669, 68669, 68670]), + col_indices=tensor([ 111, 822, 875, ..., 160, 4019, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=68670, layout=torch.sparse_csr) +tensor([0.4523, 0.8522, 0.2052, ..., 0.5999, 0.3163, 0.6791]) +Matrix: as-caida_G_004 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 68670 +Density: 6.97411089889098e-05 +Time: 10.784255027770996 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_005.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_005.json new file mode 100644 index 0000000..d0819f9 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_005.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 173924, "MATRIX_FILE": "as-caida_G_005", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 70026, "MATRIX_DENSITY": 7.111825976492498e-05, "TIME_S": 10.262417554855347, "TIME_S_1KI": 0.05900518361385057, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1066.3818225359917, "W": 102.51, "J_1KI": 6.131309207101904, "W_1KI": 0.5893953680918103, "W_D": 67.13624999999999, "J_D": 698.3989526215195, "W_D_1KI": 0.3860091189255076, "J_D_1KI": 0.0022194126108271866} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_005.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_005.output new file mode 100644 index 0000000..9ab0e3b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_005.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 63, 63, ..., 70025, 70025, 70026]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=70026, layout=torch.sparse_csr) +tensor([0.7007, 0.4071, 0.2967, ..., 0.4021, 0.5723, 0.8823]) +Matrix: as-caida_G_005 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 70026 +Density: 7.111825976492498e-05 +Time: 10.262417554855347 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_006.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_006.json new file mode 100644 index 0000000..341dca1 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_006.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 175479, "MATRIX_FILE": "as-caida_G_006", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 71094, "MATRIX_DENSITY": 7.220291834072453e-05, "TIME_S": 10.993737697601318, "TIME_S_1KI": 0.06264987660974429, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1078.2910858011246, "W": 102.06, "J_1KI": 6.144844031485959, "W_1KI": 0.5816080556647805, "W_D": 65.81275000000001, "J_D": 695.3292343431116, "W_D_1KI": 0.3750463018366871, "J_D_1KI": 0.0021372717067950414} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_006.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_006.output new file mode 100644 index 0000000..0b165bc --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_006.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 60, 60, ..., 71093, 71093, 71094]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=71094, layout=torch.sparse_csr) +tensor([0.8805, 0.4801, 0.5765, ..., 0.4309, 0.7632, 0.1367]) +Matrix: as-caida_G_006 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 71094 +Density: 7.220291834072453e-05 +Time: 10.993737697601318 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_007.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_007.json new file mode 100644 index 0000000..fa460fa --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_007.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 174611, "MATRIX_FILE": "as-caida_G_007", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 71658, "MATRIX_DENSITY": 7.277571556614678e-05, "TIME_S": 10.340533256530762, "TIME_S_1KI": 0.059220399954932744, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1062.7053595733641, "W": 102.71999999999998, "J_1KI": 6.086130653700878, "W_1KI": 0.5882790889462862, "W_D": 55.67474999999999, "J_D": 575.9915811712144, "W_D_1KI": 0.31885018698707407, "J_D_1KI": 0.0018260601393215437} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_007.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_007.output new file mode 100644 index 0000000..c70da3c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_007.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 57, 57, ..., 71657, 71657, 71658]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=71658, layout=torch.sparse_csr) +tensor([0.0021, 0.2921, 0.2062, ..., 0.5015, 0.4698, 0.4915]) +Matrix: as-caida_G_007 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 71658 +Density: 7.277571556614678e-05 +Time: 10.340533256530762 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_008.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_008.json new file mode 100644 index 0000000..9b39bd7 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_008.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 169567, "MATRIX_FILE": "as-caida_G_008", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 72140, "MATRIX_DENSITY": 7.326523376234096e-05, "TIME_S": 10.129003286361694, "TIME_S_1KI": 0.05973451960795257, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1035.8923956489562, "W": 102.31999999999998, "J_1KI": 6.109044776689781, "W_1KI": 0.6034192973868735, "W_D": 66.55324999999998, "J_D": 673.78817025727, "W_D_1KI": 0.39248939947041567, "J_D_1KI": 0.0023146567402290287} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_008.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_008.output new file mode 100644 index 0000000..ab3453d --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_008.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 55, 55, ..., 72139, 72139, 72140]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=72140, layout=torch.sparse_csr) +tensor([0.9303, 0.4502, 0.7201, ..., 0.8139, 0.9101, 0.2196]) +Matrix: as-caida_G_008 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 72140 +Density: 7.326523376234096e-05 +Time: 10.129003286361694 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_009.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_009.json new file mode 100644 index 0000000..394de40 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_009.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 176048, "MATRIX_FILE": "as-caida_G_009", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 74344, "MATRIX_DENSITY": 7.550361157232432e-05, "TIME_S": 10.2708158493042, "TIME_S_1KI": 0.05834099705366831, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1104.4738229870798, "W": 102.93, "J_1KI": 6.273708437398208, "W_1KI": 0.5846700899754612, "W_D": 67.52550000000001, "J_D": 724.5715256398917, "W_D_1KI": 0.38356300554394257, "J_D_1KI": 0.0021787410566660374} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_009.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_009.output new file mode 100644 index 0000000..fd610b1 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_009.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 38, 38, ..., 74343, 74343, 74344]), + col_indices=tensor([ 111, 875, 1040, ..., 160, 4019, 12170]), + values=tensor([4., 3., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=74344, layout=torch.sparse_csr) +tensor([0.7638, 0.5494, 0.2300, ..., 0.6978, 0.0671, 0.1075]) +Matrix: as-caida_G_009 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 74344 +Density: 7.550361157232432e-05 +Time: 10.2708158493042 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_010.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_010.json new file mode 100644 index 0000000..0212635 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_010.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 169714, "MATRIX_FILE": "as-caida_G_010", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 74994, "MATRIX_DENSITY": 7.616375021864427e-05, "TIME_S": 10.116578340530396, "TIME_S_1KI": 0.059609568689267804, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1067.3958758711815, "W": 102.55, "J_1KI": 6.289380227153808, "W_1KI": 0.6042518590098637, "W_D": 67.2245, "J_D": 699.7089620429279, "W_D_1KI": 0.3961046230717561, "J_D_1KI": 0.0023339537284593854} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_010.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_010.output new file mode 100644 index 0000000..f86afe2 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_010.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 28, 28, ..., 74993, 74993, 74994]), + col_indices=tensor([ 1040, 2020, 2054, ..., 160, 160, 12170]), + values=tensor([1., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=74994, layout=torch.sparse_csr) +tensor([0.1664, 0.0160, 0.2923, ..., 0.6532, 0.8821, 0.9493]) +Matrix: as-caida_G_010 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 74994 +Density: 7.616375021864427e-05 +Time: 10.116578340530396 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_011.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_011.json new file mode 100644 index 0000000..0bfd4b5 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_011.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 173723, "MATRIX_FILE": "as-caida_G_011", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 75118, "MATRIX_DENSITY": 7.628968436040377e-05, "TIME_S": 10.792476177215576, "TIME_S_1KI": 0.062124624702633365, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1112.626372818947, "W": 102.93, "J_1KI": 6.4046002706547025, "W_1KI": 0.5924949488553617, "W_D": 67.69250000000001, "J_D": 731.7250630724432, "W_D_1KI": 0.38965767342263263, "J_D_1KI": 0.002242982641461595} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_011.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_011.output new file mode 100644 index 0000000..4fe62ff --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_011.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 25, 25, ..., 75117, 75117, 75118]), + col_indices=tensor([ 1040, 2020, 2054, ..., 160, 160, 12170]), + values=tensor([1., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=75118, layout=torch.sparse_csr) +tensor([0.0025, 0.9718, 0.9054, ..., 0.8882, 0.0066, 0.6007]) +Matrix: as-caida_G_011 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 75118 +Density: 7.628968436040377e-05 +Time: 10.792476177215576 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_012.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_012.json new file mode 100644 index 0000000..b311bed --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_012.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 169643, "MATRIX_FILE": "as-caida_G_012", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 76530, "MATRIX_DENSITY": 7.772370861979419e-05, "TIME_S": 10.67755675315857, "TIME_S_1KI": 0.06294133417328489, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1055.80616191864, "W": 103.14, "J_1KI": 6.2236942397778865, "W_1KI": 0.6079826459093508, "W_D": 67.53649999999999, "J_D": 691.3462561025618, "W_D_1KI": 0.3981095594866867, "J_D_1KI": 0.002346749111290691} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_012.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_012.output new file mode 100644 index 0000000..ea6ab58 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_012.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 76530, 76530, 76530]), + col_indices=tensor([1040, 2054, 5699, ..., 160, 160, 7454]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=76530, layout=torch.sparse_csr) +tensor([0.6787, 0.5066, 0.1023, ..., 0.7463, 0.8577, 0.6356]) +Matrix: as-caida_G_012 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 76530 +Density: 7.772370861979419e-05 +Time: 10.67755675315857 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_013.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_013.json new file mode 100644 index 0000000..1e06709 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_013.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 166912, "MATRIX_FILE": "as-caida_G_013", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 77002, "MATRIX_DENSITY": 7.820307083681422e-05, "TIME_S": 10.320421695709229, "TIME_S_1KI": 0.061831514185374505, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1051.1990657114982, "W": 102.69, "J_1KI": 6.297923850361258, "W_1KI": 0.615234375, "W_D": 67.39025000000001, "J_D": 689.8487470840813, "W_D_1KI": 0.4037471841449387, "J_D_1KI": 0.002418922451021728} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_013.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_013.output new file mode 100644 index 0000000..e666a89 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_013.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 5, 5, ..., 77002, 77002, 77002]), + col_indices=tensor([1040, 2054, 2150, ..., 160, 8230, 7454]), + values=tensor([1., 1., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=77002, layout=torch.sparse_csr) +tensor([0.7568, 0.2849, 0.2216, ..., 0.5961, 0.2793, 0.6292]) +Matrix: as-caida_G_013 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 77002 +Density: 7.820307083681422e-05 +Time: 10.320421695709229 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_014.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_014.json new file mode 100644 index 0000000..727b4ef --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_014.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 178580, "MATRIX_FILE": "as-caida_G_014", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 75982, "MATRIX_DENSITY": 7.71671609610506e-05, "TIME_S": 11.463822364807129, "TIME_S_1KI": 0.06419432391537198, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1173.2408409786224, "W": 102.97999999999999, "J_1KI": 6.569833357479126, "W_1KI": 0.5766603203046252, "W_D": 67.63524999999998, "J_D": 770.5616390541791, "W_D_1KI": 0.3787392205174151, "J_D_1KI": 0.0021208378346814598} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_014.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_014.output new file mode 100644 index 0000000..8b156cf --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_014.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 5, 5, ..., 75982, 75982, 75982]), + col_indices=tensor([1040, 2054, 2150, ..., 160, 160, 8230]), + values=tensor([1., 1., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=75982, layout=torch.sparse_csr) +tensor([0.7554, 0.0193, 0.8398, ..., 0.5303, 0.5195, 0.4780]) +Matrix: as-caida_G_014 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 75982 +Density: 7.71671609610506e-05 +Time: 11.463822364807129 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_015.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_015.json new file mode 100644 index 0000000..572ecf2 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_015.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 169292, "MATRIX_FILE": "as-caida_G_015", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 77124, "MATRIX_DENSITY": 7.832697378273889e-05, "TIME_S": 10.522574663162231, "TIME_S_1KI": 0.062156360980803765, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1090.2590997695922, "W": 102.56, "J_1KI": 6.4401099861162505, "W_1KI": 0.6058171679701345, "W_D": 67.33975000000001, "J_D": 715.8519424113632, "W_D_1KI": 0.3977727831202893, "J_D_1KI": 0.0023496253994299155} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_015.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_015.output new file mode 100644 index 0000000..a6f7b1c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_015.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 4, 4, ..., 77124, 77124, 77124]), + col_indices=tensor([1040, 2054, 4842, ..., 160, 160, 8230]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=77124, layout=torch.sparse_csr) +tensor([0.6125, 0.0383, 0.5217, ..., 0.7441, 0.5372, 0.0416]) +Matrix: as-caida_G_015 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 77124 +Density: 7.832697378273889e-05 +Time: 10.522574663162231 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_016.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_016.json new file mode 100644 index 0000000..00be471 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_016.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 168722, "MATRIX_FILE": "as-caida_G_016", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 77860, "MATRIX_DENSITY": 7.907445384995657e-05, "TIME_S": 10.318783521652222, "TIME_S_1KI": 0.06115849457481669, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1085.4636900424957, "W": 103.0, "J_1KI": 6.433444897775606, "W_1KI": 0.6104716634463793, "W_D": 67.864, "J_D": 715.183571466446, "W_D_1KI": 0.4022237763895639, "J_D_1KI": 0.0023839438626235103} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_016.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_016.output new file mode 100644 index 0000000..2ec4883 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_016.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 77856, 77858, 77860]), + col_indices=tensor([ 1040, 4842, 5699, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=77860, layout=torch.sparse_csr) +tensor([0.9836, 0.4148, 0.1062, ..., 0.6174, 0.5100, 0.1410]) +Matrix: as-caida_G_016 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 77860 +Density: 7.907445384995657e-05 +Time: 10.318783521652222 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_017.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_017.json new file mode 100644 index 0000000..db057f1 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_017.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 168591, "MATRIX_FILE": "as-caida_G_017", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 79718, "MATRIX_DENSITY": 8.096143478051423e-05, "TIME_S": 10.256053686141968, "TIME_S_1KI": 0.06083393352042498, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1083.0131065940857, "W": 103.46, "J_1KI": 6.423908195538822, "W_1KI": 0.6136745140606557, "W_D": 68.22774999999999, "J_D": 714.2040158846377, "W_D_1KI": 0.404693904182311, "J_D_1KI": 0.0024004478541696235} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_017.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_017.output new file mode 100644 index 0000000..f647277 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_017.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 79714, 79716, 79718]), + col_indices=tensor([ 1040, 5699, 33, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 4., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=79718, layout=torch.sparse_csr) +tensor([0.1112, 0.8123, 0.5927, ..., 0.6080, 0.0833, 0.9353]) +Matrix: as-caida_G_017 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 79718 +Density: 8.096143478051423e-05 +Time: 10.256053686141968 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_018.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_018.json new file mode 100644 index 0000000..7c81a4f --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_018.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 166040, "MATRIX_FILE": "as-caida_G_018", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 80396, "MATRIX_DENSITY": 8.16500101685218e-05, "TIME_S": 10.737539291381836, "TIME_S_1KI": 0.06466838889051937, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1030.8235529851913, "W": 103.53, "J_1KI": 6.208284467508982, "W_1KI": 0.6235244519392917, "W_D": 68.04225000000001, "J_D": 677.4804781039954, "W_D_1KI": 0.40979432666827276, "J_D_1KI": 0.0024680458122637483} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_018.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_018.output new file mode 100644 index 0000000..996004a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_018.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 80392, 80394, 80396]), + col_indices=tensor([ 1040, 5282, 5699, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=80396, layout=torch.sparse_csr) +tensor([0.0372, 0.6591, 0.7169, ..., 0.1222, 0.6859, 0.3011]) +Matrix: as-caida_G_018 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 80396 +Density: 8.16500101685218e-05 +Time: 10.737539291381836 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_019.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_019.json new file mode 100644 index 0000000..e61485f --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_019.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 165751, "MATRIX_FILE": "as-caida_G_019", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 80970, "MATRIX_DENSITY": 8.22329633731182e-05, "TIME_S": 10.490274906158447, "TIME_S_1KI": 0.06328936118731379, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1066.877656738758, "W": 103.29, "J_1KI": 6.436628778944067, "W_1KI": 0.6231636611543823, "W_D": 68.08575000000002, "J_D": 703.2545785390737, "W_D_1KI": 0.4107712773980248, "J_D_1KI": 0.0024782431321562154} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_019.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_019.output new file mode 100644 index 0000000..8e168d4 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_019.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 80966, 80968, 80970]), + col_indices=tensor([ 1040, 5699, 106, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=80970, layout=torch.sparse_csr) +tensor([0.0615, 0.7682, 0.7020, ..., 0.3174, 0.0798, 0.9931]) +Matrix: as-caida_G_019 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 80970 +Density: 8.22329633731182e-05 +Time: 10.490274906158447 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_020.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_020.json new file mode 100644 index 0000000..8e6ce6a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_020.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 165475, "MATRIX_FILE": "as-caida_G_020", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 80948, "MATRIX_DENSITY": 8.221062021893506e-05, "TIME_S": 10.475436449050903, "TIME_S_1KI": 0.06330525124067626, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1069.9323037838935, "W": 103.39, "J_1KI": 6.465824467647038, "W_1KI": 0.6248073727149116, "W_D": 68.40975, "J_D": 707.9388859539629, "W_D_1KI": 0.4134144130533313, "J_D_1KI": 0.002498349678521416} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_020.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_020.output new file mode 100644 index 0000000..fc98277 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_020.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 80944, 80946, 80948]), + col_indices=tensor([ 1040, 5699, 106, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=80948, layout=torch.sparse_csr) +tensor([0.6278, 0.4024, 0.1138, ..., 0.2626, 0.4452, 0.6451]) +Matrix: as-caida_G_020 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 80948 +Density: 8.221062021893506e-05 +Time: 10.475436449050903 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_021.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_021.json new file mode 100644 index 0000000..8249522 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_021.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 169404, "MATRIX_FILE": "as-caida_G_021", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 81882, "MATRIX_DENSITY": 8.315918867380097e-05, "TIME_S": 10.59764814376831, "TIME_S_1KI": 0.06255842922108279, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1107.759307665825, "W": 102.87, "J_1KI": 6.539156735766717, "W_1KI": 0.6072465821350146, "W_D": 67.45375, "J_D": 726.3781413382292, "W_D_1KI": 0.3981827465703289, "J_D_1KI": 0.002350491998833138} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_021.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_021.output new file mode 100644 index 0000000..85de6d6 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_021.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 81878, 81880, 81882]), + col_indices=tensor([ 1040, 5699, 106, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=81882, layout=torch.sparse_csr) +tensor([0.6064, 0.2542, 0.6746, ..., 0.1324, 0.2222, 0.7940]) +Matrix: as-caida_G_021 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 81882 +Density: 8.315918867380097e-05 +Time: 10.59764814376831 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_022.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_022.json new file mode 100644 index 0000000..2df290c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_022.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 167837, "MATRIX_FILE": "as-caida_G_022", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 82138, "MATRIX_DENSITY": 8.341918174065929e-05, "TIME_S": 10.677026987075806, "TIME_S_1KI": 0.06361545420304109, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1119.1531069946288, "W": 103.36, "J_1KI": 6.6680952769331485, "W_1KI": 0.6158356023999475, "W_D": 67.59975, "J_D": 731.9511440069675, "W_D_1KI": 0.40277024732329586, "J_D_1KI": 0.0023997702969148394} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_022.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_022.output new file mode 100644 index 0000000..3e64b3a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_022.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 82134, 82136, 82138]), + col_indices=tensor([ 106, 329, 1040, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=82138, layout=torch.sparse_csr) +tensor([0.9057, 0.0410, 0.1754, ..., 0.9320, 0.8831, 0.5332]) +Matrix: as-caida_G_022 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 82138 +Density: 8.341918174065929e-05 +Time: 10.677026987075806 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_023.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_023.json new file mode 100644 index 0000000..54c227e --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_023.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 169758, "MATRIX_FILE": "as-caida_G_023", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 83524, "MATRIX_DENSITY": 8.482680045419692e-05, "TIME_S": 10.913155555725098, "TIME_S_1KI": 0.06428654647041729, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1145.642321052551, "W": 103.95999999999998, "J_1KI": 6.748679420425258, "W_1KI": 0.6124011828603069, "W_D": 68.57974999999998, "J_D": 755.7509038784501, "W_D_1KI": 0.4039853791868423, "J_D_1KI": 0.002379772259256367} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_023.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_023.output new file mode 100644 index 0000000..9a4917e --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_023.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 83520, 83522, 83524]), + col_indices=tensor([ 106, 329, 1040, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=83524, layout=torch.sparse_csr) +tensor([0.9464, 0.7481, 0.6110, ..., 0.1460, 0.3305, 0.7149]) +Matrix: as-caida_G_023 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 83524 +Density: 8.482680045419692e-05 +Time: 10.913155555725098 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_024.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_024.json new file mode 100644 index 0000000..4ff75dc --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_024.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 176615, "MATRIX_FILE": "as-caida_G_024", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 83640, "MATRIX_DENSITY": 8.49446098126171e-05, "TIME_S": 11.617779970169067, "TIME_S_1KI": 0.06578025632120187, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1195.342978055477, "W": 103.91, "J_1KI": 6.768071670330816, "W_1KI": 0.5883418735667978, "W_D": 67.8685, "J_D": 780.7346252156495, "W_D_1KI": 0.38427370268663474, "J_D_1KI": 0.002175770476384422} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_024.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_024.output new file mode 100644 index 0000000..21ca2d3 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_024.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 83636, 83638, 83640]), + col_indices=tensor([ 106, 329, 1040, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=83640, layout=torch.sparse_csr) +tensor([0.5890, 0.4209, 0.5244, ..., 0.7521, 0.2185, 0.1105]) +Matrix: as-caida_G_024 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 83640 +Density: 8.49446098126171e-05 +Time: 11.617779970169067 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_025.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_025.json new file mode 100644 index 0000000..ac5f9c1 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_025.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 156745, "MATRIX_FILE": "as-caida_G_025", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85850, "MATRIX_DENSITY": 8.718908121010495e-05, "TIME_S": 10.202822208404541, "TIME_S_1KI": 0.06509185114934793, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1069.05028301239, "W": 103.44, "J_1KI": 6.820315053190788, "W_1KI": 0.6599253564707008, "W_D": 67.67325, "J_D": 699.4016537593602, "W_D_1KI": 0.4317410443714313, "J_D_1KI": 0.0027544166918972296} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_025.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_025.output new file mode 100644 index 0000000..fa36435 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_025.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 85845, 85847, 85850]), + col_indices=tensor([ 346, 13811, 21783, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=85850, layout=torch.sparse_csr) +tensor([0.4404, 0.1008, 0.8562, ..., 0.6741, 0.2809, 0.4100]) +Matrix: as-caida_G_025 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85850 +Density: 8.718908121010495e-05 +Time: 10.202822208404541 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_026.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_026.json new file mode 100644 index 0000000..1122f64 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_026.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 165395, "MATRIX_FILE": "as-caida_G_026", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85468, "MATRIX_DENSITY": 8.68011228056523e-05, "TIME_S": 10.84380054473877, "TIME_S_1KI": 0.06556304933485758, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1123.5689677715302, "W": 103.42, "J_1KI": 6.79324627571287, "W_1KI": 0.6252909701018773, "W_D": 67.86625000000001, "J_D": 737.3081846743823, "W_D_1KI": 0.4103283049668975, "J_D_1KI": 0.0024808990898569938} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_026.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_026.output new file mode 100644 index 0000000..97c29aa --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_026.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 85463, 85465, 85468]), + col_indices=tensor([21783, 106, 329, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=85468, layout=torch.sparse_csr) +tensor([0.8052, 0.7836, 0.4395, ..., 0.6789, 0.0405, 0.5072]) +Matrix: as-caida_G_026 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85468 +Density: 8.68011228056523e-05 +Time: 10.84380054473877 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_027.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_027.json new file mode 100644 index 0000000..fbcef75 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_027.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 163309, "MATRIX_FILE": "as-caida_G_027", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85744, "MATRIX_DENSITY": 8.708142783085892e-05, "TIME_S": 10.494378328323364, "TIME_S_1KI": 0.06426086944579518, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1126.001567387581, "W": 103.62, "J_1KI": 6.894914348796337, "W_1KI": 0.634502691217263, "W_D": 68.42600000000002, "J_D": 743.5609269452096, "W_D_1KI": 0.4189971158968582, "J_D_1KI": 0.0025656706972479056} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_027.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_027.output new file mode 100644 index 0000000..472b0c0 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_027.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 85739, 85741, 85744]), + col_indices=tensor([21783, 106, 329, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=85744, layout=torch.sparse_csr) +tensor([0.0054, 0.2269, 0.5117, ..., 0.3972, 0.0962, 0.5164]) +Matrix: as-caida_G_027 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85744 +Density: 8.708142783085892e-05 +Time: 10.494378328323364 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_028.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_028.json new file mode 100644 index 0000000..741810b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_028.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 163227, "MATRIX_FILE": "as-caida_G_028", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 84962, "MATRIX_DENSITY": 8.628723025944015e-05, "TIME_S": 10.650424718856812, "TIME_S_1KI": 0.0652491604872773, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1103.2409412288666, "W": 103.08, "J_1KI": 6.758936580522013, "W_1KI": 0.6315131687772244, "W_D": 67.741, "J_D": 725.0159545962811, "W_D_1KI": 0.41501099695516064, "J_D_1KI": 0.0025425388995396632} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_028.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_028.output new file mode 100644 index 0000000..37773f5 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_028.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 84957, 84959, 84962]), + col_indices=tensor([ 1809, 21783, 106, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=84962, layout=torch.sparse_csr) +tensor([0.4538, 0.5406, 0.4211, ..., 0.9584, 0.9196, 0.2702]) +Matrix: as-caida_G_028 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 84962 +Density: 8.628723025944015e-05 +Time: 10.650424718856812 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_029.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_029.json new file mode 100644 index 0000000..1d1c072 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_029.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 166573, "MATRIX_FILE": "as-caida_G_029", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 86566, "MATRIX_DENSITY": 8.791624931897431e-05, "TIME_S": 10.520256519317627, "TIME_S_1KI": 0.06315703336865894, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1109.3037847280502, "W": 103.95, "J_1KI": 6.659565384114174, "W_1KI": 0.6240507165026745, "W_D": 68.76575, "J_D": 733.8346006220579, "W_D_1KI": 0.4128265084977757, "J_D_1KI": 0.0024783518847458813} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_029.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_029.output new file mode 100644 index 0000000..8633797 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_029.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 86561, 86563, 86566]), + col_indices=tensor([ 1809, 21783, 106, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=86566, layout=torch.sparse_csr) +tensor([0.7401, 0.0999, 0.8090, ..., 0.1335, 0.0509, 0.5062]) +Matrix: as-caida_G_029 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 86566 +Density: 8.791624931897431e-05 +Time: 10.520256519317627 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_030.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_030.json new file mode 100644 index 0000000..8aa56e6 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_030.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 161185, "MATRIX_FILE": "as-caida_G_030", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 86850, "MATRIX_DENSITY": 8.820467912752026e-05, "TIME_S": 10.397324800491333, "TIME_S_1KI": 0.06450553587797458, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1098.2305766177178, "W": 103.01, "J_1KI": 6.813478776671017, "W_1KI": 0.6390793187951733, "W_D": 67.52074999999999, "J_D": 719.8655684512257, "W_D_1KI": 0.41890219313211524, "J_D_1KI": 0.0025988906730286024} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_030.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_030.output new file mode 100644 index 0000000..f071357 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_030.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 86850, 86850, 86850]), + col_indices=tensor([ 1809, 21783, 106, ..., 7018, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=86850, layout=torch.sparse_csr) +tensor([0.3098, 0.1963, 0.0293, ..., 0.2597, 0.0091, 0.1943]) +Matrix: as-caida_G_030 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 86850 +Density: 8.820467912752026e-05 +Time: 10.397324800491333 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_031.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_031.json new file mode 100644 index 0000000..77e43be --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_031.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 164806, "MATRIX_FILE": "as-caida_G_031", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87232, "MATRIX_DENSITY": 8.859263753197291e-05, "TIME_S": 10.999683141708374, "TIME_S_1KI": 0.0667432201601178, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1135.960792825222, "W": 103.38999999999999, "J_1KI": 6.892715027518549, "W_1KI": 0.6273436646724027, "W_D": 67.54274999999998, "J_D": 742.101903855264, "W_D_1KI": 0.40983186291761214, "J_D_1KI": 0.0024867532912491784} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_031.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_031.output new file mode 100644 index 0000000..21327d8 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_031.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87232, 87232, 87232]), + col_indices=tensor([ 1809, 21783, 106, ..., 1101, 16290, 882]), + values=tensor([1., 1., 1., ..., 2., 1., 1.]), size=(31379, 31379), + nnz=87232, layout=torch.sparse_csr) +tensor([0.2768, 0.2165, 0.7894, ..., 0.9356, 0.8180, 0.0912]) +Matrix: as-caida_G_031 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87232 +Density: 8.859263753197291e-05 +Time: 10.999683141708374 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_032.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_032.json new file mode 100644 index 0000000..c2e7eb3 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_032.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 160966, "MATRIX_FILE": "as-caida_G_032", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87938, "MATRIX_DENSITY": 8.930964966166813e-05, "TIME_S": 10.586175441741943, "TIME_S_1KI": 0.06576653107949469, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1116.0250046110154, "W": 103.26, "J_1KI": 6.933296501192895, "W_1KI": 0.6415019320850366, "W_D": 67.93825000000001, "J_D": 734.2706349943281, "W_D_1KI": 0.42206583999105407, "J_D_1KI": 0.0026220806877915465} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_032.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_032.output new file mode 100644 index 0000000..9bd7595 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_032.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87938, 87938, 87938]), + col_indices=tensor([ 1809, 21783, 106, ..., 160, 16290, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87938, layout=torch.sparse_csr) +tensor([0.0820, 0.8237, 0.1857, ..., 0.2676, 0.1843, 0.1059]) +Matrix: as-caida_G_032 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87938 +Density: 8.930964966166813e-05 +Time: 10.586175441741943 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_033.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_033.json new file mode 100644 index 0000000..a52d931 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_033.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 165032, "MATRIX_FILE": "as-caida_G_033", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87784, "MATRIX_DENSITY": 8.915324758238617e-05, "TIME_S": 10.995254278182983, "TIME_S_1KI": 0.06662498350733786, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1136.206867132187, "W": 104.33000000000001, "J_1KI": 6.884766997504647, "W_1KI": 0.6321804256144263, "W_D": 68.88100000000001, "J_D": 750.149192130089, "W_D_1KI": 0.41737965970236085, "J_D_1KI": 0.0025290832063015706} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_033.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_033.output new file mode 100644 index 0000000..6ada3b3 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_033.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87784, 87784, 87784]), + col_indices=tensor([ 1809, 21783, 106, ..., 160, 16290, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87784, layout=torch.sparse_csr) +tensor([0.7467, 0.1233, 0.7407, ..., 0.8280, 0.9580, 0.7186]) +Matrix: as-caida_G_033 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87784 +Density: 8.915324758238617e-05 +Time: 10.995254278182983 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_034.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_034.json new file mode 100644 index 0000000..cf4532b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_034.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 162469, "MATRIX_FILE": "as-caida_G_034", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88490, "MATRIX_DENSITY": 8.987025971208138e-05, "TIME_S": 10.796740293502808, "TIME_S_1KI": 0.06645415613749582, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1131.3086612319946, "W": 104.16, "J_1KI": 6.963227823350883, "W_1KI": 0.6411069188583668, "W_D": 68.79624999999999, "J_D": 747.2138391444086, "W_D_1KI": 0.4234423182268616, "J_D_1KI": 0.002606296082494886} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_034.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_034.output new file mode 100644 index 0000000..42d8a09 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_034.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 88489, 88489, 88490]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88490, layout=torch.sparse_csr) +tensor([0.3760, 0.5984, 0.7516, ..., 0.6783, 0.9547, 0.7081]) +Matrix: as-caida_G_034 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88490 +Density: 8.987025971208138e-05 +Time: 10.796740293502808 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_035.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_035.json new file mode 100644 index 0000000..4ec8576 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_035.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 163485, "MATRIX_FILE": "as-caida_G_035", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87560, "MATRIX_DENSITY": 8.892575364888514e-05, "TIME_S": 10.652968645095825, "TIME_S_1KI": 0.0651617496718098, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1174.8555218696595, "W": 103.14, "J_1KI": 7.186319979629076, "W_1KI": 0.6308835672997523, "W_D": 67.85825, "J_D": 772.9652871525287, "W_D_1KI": 0.4150732483102425, "J_D_1KI": 0.0025389072288604} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_035.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_035.output new file mode 100644 index 0000000..fd5a1fc --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_035.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87559, 87559, 87560]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87560, layout=torch.sparse_csr) +tensor([0.1921, 0.3588, 0.2207, ..., 0.9642, 0.5418, 0.1348]) +Matrix: as-caida_G_035 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87560 +Density: 8.892575364888514e-05 +Time: 10.652968645095825 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_036.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_036.json new file mode 100644 index 0000000..0db2a98 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_036.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 168306, "MATRIX_FILE": "as-caida_G_036", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88616, "MATRIX_DENSITY": 8.999822504967571e-05, "TIME_S": 10.902535915374756, "TIME_S_1KI": 0.0647780585087564, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1143.7132000613212, "W": 103.99, "J_1KI": 6.795439259808451, "W_1KI": 0.6178627024586171, "W_D": 68.89675, "J_D": 757.7471143025756, "W_D_1KI": 0.40935409313987614, "J_D_1KI": 0.002432201425616889} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_036.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_036.output new file mode 100644 index 0000000..cae2e13 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_036.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 88615, 88615, 88616]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88616, layout=torch.sparse_csr) +tensor([0.6596, 0.3928, 0.4843, ..., 0.3029, 0.8374, 0.3544]) +Matrix: as-caida_G_036 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88616 +Density: 8.999822504967571e-05 +Time: 10.902535915374756 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_037.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_037.json new file mode 100644 index 0000000..750dc3d --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_037.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 162795, "MATRIX_FILE": "as-caida_G_037", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88654, "MATRIX_DENSITY": 9.003681777053749e-05, "TIME_S": 10.765100717544556, "TIME_S_1KI": 0.06612672820138552, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1160.6145133686066, "W": 103.16, "J_1KI": 7.129300736316266, "W_1KI": 0.6336803955895451, "W_D": 67.89375, "J_D": 763.847146345675, "W_D_1KI": 0.41705058509167975, "J_D_1KI": 0.0025618144604667202} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_037.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_037.output new file mode 100644 index 0000000..322dea5 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_037.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 88653, 88653, 88654]), + col_indices=tensor([ 1809, 106, 329, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88654, layout=torch.sparse_csr) +tensor([0.7736, 0.7913, 0.6185, ..., 0.6892, 0.7991, 0.4111]) +Matrix: as-caida_G_037 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88654 +Density: 9.003681777053749e-05 +Time: 10.765100717544556 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_038.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_038.json new file mode 100644 index 0000000..1b03258 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_038.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 160910, "MATRIX_FILE": "as-caida_G_038", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88644, "MATRIX_DENSITY": 9.002666179136334e-05, "TIME_S": 10.396665573120117, "TIME_S_1KI": 0.06461168089689963, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1130.0299159669876, "W": 103.34, "J_1KI": 7.022745111969346, "W_1KI": 0.642222360325648, "W_D": 68.16325, "J_D": 745.369766494453, "W_D_1KI": 0.4236110247964701, "J_D_1KI": 0.0026325960151418193} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_038.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_038.output new file mode 100644 index 0000000..4f2ceac --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_038.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 88643, 88643, 88644]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88644, layout=torch.sparse_csr) +tensor([0.1430, 0.9858, 0.3715, ..., 0.6229, 0.1589, 0.5023]) +Matrix: as-caida_G_038 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88644 +Density: 9.002666179136334e-05 +Time: 10.396665573120117 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_039.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_039.json new file mode 100644 index 0000000..67f8069 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_039.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 158023, "MATRIX_FILE": "as-caida_G_039", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87804, "MATRIX_DENSITY": 8.917355954073447e-05, "TIME_S": 10.361143589019775, "TIME_S_1KI": 0.0655673135494186, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1102.5796518707275, "W": 103.63, "J_1KI": 6.977336538799589, "W_1KI": 0.6557906127589022, "W_D": 68.24699999999999, "J_D": 726.1194007644651, "W_D_1KI": 0.4318801693424374, "J_D_1KI": 0.0027330209484849512} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_039.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_039.output new file mode 100644 index 0000000..141b4fa --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_039.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 87803, 87803, 87804]), + col_indices=tensor([ 1809, 106, 329, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87804, layout=torch.sparse_csr) +tensor([0.2527, 0.1288, 0.9201, ..., 0.9294, 0.3560, 0.3952]) +Matrix: as-caida_G_039 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87804 +Density: 8.917355954073447e-05 +Time: 10.361143589019775 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_040.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_040.json new file mode 100644 index 0000000..0ebad49 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_040.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 156775, "MATRIX_FILE": "as-caida_G_040", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89658, "MATRIX_DENSITY": 9.105647807962247e-05, "TIME_S": 10.213602781295776, "TIME_S_1KI": 0.06514815998275093, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1061.906050515175, "W": 103.65, "J_1KI": 6.77343996501467, "W_1KI": 0.6611385743900494, "W_D": 68.55775, "J_D": 702.3819540251493, "W_D_1KI": 0.4373002710891405, "J_D_1KI": 0.002789349520581346} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_040.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_040.output new file mode 100644 index 0000000..9b02adb --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_040.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89657, 89657, 89658]), + col_indices=tensor([ 106, 329, 1040, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89658, layout=torch.sparse_csr) +tensor([0.5314, 0.7165, 0.6612, ..., 0.8549, 0.8720, 0.1732]) +Matrix: as-caida_G_040 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89658 +Density: 9.105647807962247e-05 +Time: 10.213602781295776 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_041.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_041.json new file mode 100644 index 0000000..54c4e5e --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_041.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 156242, "MATRIX_FILE": "as-caida_G_041", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88944, "MATRIX_DENSITY": 9.033134116658794e-05, "TIME_S": 10.548433065414429, "TIME_S_1KI": 0.06751342830618162, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1103.8951300406457, "W": 103.89, "J_1KI": 7.065290575137579, "W_1KI": 0.6649300444182742, "W_D": 68.55675, "J_D": 728.4576230283379, "W_D_1KI": 0.43878566582609024, "J_D_1KI": 0.0028083720499359342} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_041.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_041.output new file mode 100644 index 0000000..f10470d --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_041.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 88943, 88943, 88944]), + col_indices=tensor([ 106, 329, 1040, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88944, layout=torch.sparse_csr) +tensor([0.3798, 0.1469, 0.6471, ..., 0.3699, 0.7177, 0.7336]) +Matrix: as-caida_G_041 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88944 +Density: 9.033134116658794e-05 +Time: 10.548433065414429 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_042.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_042.json new file mode 100644 index 0000000..3fdb195 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_042.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 163963, "MATRIX_FILE": "as-caida_G_042", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89176, "MATRIX_DENSITY": 9.056695988342829e-05, "TIME_S": 10.648859024047852, "TIME_S_1KI": 0.06494671983342494, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1123.849936594963, "W": 103.94, "J_1KI": 6.854289910497876, "W_1KI": 0.6339235071327068, "W_D": 68.12174999999999, "J_D": 736.5655610759853, "W_D_1KI": 0.4154702585339375, "J_D_1KI": 0.002533926913595979} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_042.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_042.output new file mode 100644 index 0000000..e0ea829 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_042.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89173, 89173, 89176]), + col_indices=tensor([ 106, 329, 1040, ..., 2232, 5295, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=89176, layout=torch.sparse_csr) +tensor([0.8708, 0.0042, 0.2958, ..., 0.3234, 0.9880, 0.1425]) +Matrix: as-caida_G_042 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89176 +Density: 9.056695988342829e-05 +Time: 10.648859024047852 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_043.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_043.json new file mode 100644 index 0000000..e876353 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_043.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 158089, "MATRIX_FILE": "as-caida_G_043", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89678, "MATRIX_DENSITY": 9.107679003797077e-05, "TIME_S": 10.285163402557373, "TIME_S_1KI": 0.06505932356177453, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1077.5548903465271, "W": 103.60000000000001, "J_1KI": 6.816128195804434, "W_1KI": 0.6553270626039763, "W_D": 68.33550000000001, "J_D": 710.7649827150108, "W_D_1KI": 0.4322596765113323, "J_D_1KI": 0.0027342805414123203} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_043.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_043.output new file mode 100644 index 0000000..cb40a08 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_043.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89676, 89676, 89678]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89678, layout=torch.sparse_csr) +tensor([0.2640, 0.5789, 0.2869, ..., 0.3390, 0.9164, 0.5273]) +Matrix: as-caida_G_043 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89678 +Density: 9.107679003797077e-05 +Time: 10.285163402557373 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_044.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_044.json new file mode 100644 index 0000000..897875d --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_044.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 162056, "MATRIX_FILE": "as-caida_G_044", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89560, "MATRIX_DENSITY": 9.095694948371577e-05, "TIME_S": 10.751084566116333, "TIME_S_1KI": 0.06634178658066553, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1102.1545347332956, "W": 104.37000000000002, "J_1KI": 6.801072066034553, "W_1KI": 0.644036629313324, "W_D": 68.92475000000002, "J_D": 727.8502037736775, "W_D_1KI": 0.425314397492225, "J_D_1KI": 0.0026244902841747607} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_044.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_044.output new file mode 100644 index 0000000..9fad2e6 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_044.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 89559, 89559, 89560]), + col_indices=tensor([ 5326, 106, 329, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89560, layout=torch.sparse_csr) +tensor([0.0951, 0.7141, 0.4812, ..., 0.1044, 0.7337, 0.2733]) +Matrix: as-caida_G_044 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89560 +Density: 9.095694948371577e-05 +Time: 10.751084566116333 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_045.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_045.json new file mode 100644 index 0000000..dfb2678 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_045.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 158140, "MATRIX_FILE": "as-caida_G_045", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89152, "MATRIX_DENSITY": 9.054258553341032e-05, "TIME_S": 10.236832618713379, "TIME_S_1KI": 0.06473272175738826, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1087.573292889595, "W": 103.53999999999999, "J_1KI": 6.877281477738681, "W_1KI": 0.6547363095990894, "W_D": 67.56249999999999, "J_D": 709.6694089323281, "W_D_1KI": 0.42723219931706075, "J_D_1KI": 0.002701607432130143} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_045.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_045.output new file mode 100644 index 0000000..e01b4f7 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_045.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89150, 89150, 89152]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89152, layout=torch.sparse_csr) +tensor([0.8982, 0.4210, 0.7569, ..., 0.5098, 0.3046, 0.1629]) +Matrix: as-caida_G_045 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89152 +Density: 9.054258553341032e-05 +Time: 10.236832618713379 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_046.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_046.json new file mode 100644 index 0000000..1434530 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_046.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 159988, "MATRIX_FILE": "as-caida_G_046", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90172, "MATRIX_DENSITY": 9.157849540917394e-05, "TIME_S": 10.25074052810669, "TIME_S_1KI": 0.06407193369569399, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1080.929725856781, "W": 103.92, "J_1KI": 6.756317510418163, "W_1KI": 0.6495487161537116, "W_D": 68.10499999999999, "J_D": 708.3979886400699, "W_D_1KI": 0.4256881766132459, "J_D_1KI": 0.002660750660132297} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_046.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_046.output new file mode 100644 index 0000000..bcb303a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_046.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 90170, 90170, 90172]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90172, layout=torch.sparse_csr) +tensor([0.0144, 0.4541, 0.5918, ..., 0.9632, 0.4185, 0.6354]) +Matrix: as-caida_G_046 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90172 +Density: 9.157849540917394e-05 +Time: 10.25074052810669 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_047.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_047.json new file mode 100644 index 0000000..d0e4988 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_047.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 168796, "MATRIX_FILE": "as-caida_G_047", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90002, "MATRIX_DENSITY": 9.140584376321335e-05, "TIME_S": 10.777946472167969, "TIME_S_1KI": 0.06385190687082613, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1177.652207751274, "W": 104.42, "J_1KI": 6.9767779316528475, "W_1KI": 0.6186165548946658, "W_D": 68.46775, "J_D": 772.1815451758504, "W_D_1KI": 0.40562424465034713, "J_D_1KI": 0.0024030441755156944} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_047.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_047.output new file mode 100644 index 0000000..f418486 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_047.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90000, 90000, 90002]), + col_indices=tensor([ 5326, 106, 329, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90002, layout=torch.sparse_csr) +tensor([0.5337, 0.7337, 0.8940, ..., 0.9281, 0.1913, 0.2346]) +Matrix: as-caida_G_047 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90002 +Density: 9.140584376321335e-05 +Time: 10.777946472167969 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_048.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_048.json new file mode 100644 index 0000000..cf4be65 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_048.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 152000, "MATRIX_FILE": "as-caida_G_048", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90820, "MATRIX_DENSITY": 9.223660285965907e-05, "TIME_S": 11.16935920715332, "TIME_S_1KI": 0.07348262636285079, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1047.4151738166809, "W": 103.88, "J_1KI": 6.890889301425532, "W_1KI": 0.6834210526315789, "W_D": 68.25925, "J_D": 688.2535060006379, "W_D_1KI": 0.4490740131578947, "J_D_1KI": 0.0029544342970914124} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_048.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_048.output new file mode 100644 index 0000000..bbe3675 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_048.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 90816, 90816, 90820]), + col_indices=tensor([ 106, 329, 1040, ..., 3562, 13498, 16085]), + values=tensor([1., 1., 1., ..., 3., 3., 3.]), size=(31379, 31379), + nnz=90820, layout=torch.sparse_csr) +tensor([0.1655, 0.9482, 0.5383, ..., 0.1963, 0.6749, 0.6744]) +Matrix: as-caida_G_048 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90820 +Density: 9.223660285965907e-05 +Time: 11.16935920715332 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_049.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_049.json new file mode 100644 index 0000000..ecba072 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_049.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 160273, "MATRIX_FILE": "as-caida_G_049", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90784, "MATRIX_DENSITY": 9.220004133463212e-05, "TIME_S": 10.464547395706177, "TIME_S_1KI": 0.06529201671963572, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1109.435533440113, "W": 104.13, "J_1KI": 6.922161146544415, "W_1KI": 0.649703942647857, "W_D": 68.53949999999999, "J_D": 730.2425501221418, "W_D_1KI": 0.4276422104783712, "J_D_1KI": 0.002668211180163666} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_049.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_049.output new file mode 100644 index 0000000..58d8d8d --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_049.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90780, 90780, 90784]), + col_indices=tensor([ 5326, 106, 329, ..., 3562, 13498, 16085]), + values=tensor([1., 1., 1., ..., 3., 3., 3.]), size=(31379, 31379), + nnz=90784, layout=torch.sparse_csr) +tensor([0.6945, 0.0285, 0.0505, ..., 0.2440, 0.1673, 0.1910]) +Matrix: as-caida_G_049 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90784 +Density: 9.220004133463212e-05 +Time: 10.464547395706177 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_050.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_050.json new file mode 100644 index 0000000..cd42ea0 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_050.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 164118, "MATRIX_FILE": "as-caida_G_050", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90392, "MATRIX_DENSITY": 9.180192695100532e-05, "TIME_S": 10.73277735710144, "TIME_S_1KI": 0.06539671064174217, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1140.4563850736617, "W": 104.11, "J_1KI": 6.949002455999109, "W_1KI": 0.6343606429520223, "W_D": 68.88, "J_D": 754.5349707412719, "W_D_1KI": 0.4196980221547911, "J_D_1KI": 0.0025572942770128266} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_050.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_050.output new file mode 100644 index 0000000..1c9be60 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_050.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90390, 90390, 90392]), + col_indices=tensor([ 5326, 106, 329, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90392, layout=torch.sparse_csr) +tensor([0.5953, 0.7085, 0.4746, ..., 0.9494, 0.0687, 0.4338]) +Matrix: as-caida_G_050 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90392 +Density: 9.180192695100532e-05 +Time: 10.73277735710144 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_051.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_051.json new file mode 100644 index 0000000..c288031 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_051.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 166689, "MATRIX_FILE": "as-caida_G_051", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90100, "MATRIX_DENSITY": 9.150537235912004e-05, "TIME_S": 10.970768213272095, "TIME_S_1KI": 0.06581578996377742, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1166.9149348139763, "W": 103.85, "J_1KI": 7.000551534978171, "W_1KI": 0.6230165157868846, "W_D": 68.633, "J_D": 771.1976188838481, "W_D_1KI": 0.4117428264612542, "J_D_1KI": 0.002470125961888632} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_051.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_051.output new file mode 100644 index 0000000..a7c736c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_051.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90098, 90098, 90100]), + col_indices=tensor([ 5326, 106, 329, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90100, layout=torch.sparse_csr) +tensor([0.8301, 0.7468, 0.6631, ..., 0.0873, 0.8108, 0.0132]) +Matrix: as-caida_G_051 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90100 +Density: 9.150537235912004e-05 +Time: 10.970768213272095 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_052.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_052.json new file mode 100644 index 0000000..52e4884 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_052.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 162221, "MATRIX_FILE": "as-caida_G_052", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 91100, "MATRIX_DENSITY": 9.252097027653536e-05, "TIME_S": 11.029372453689575, "TIME_S_1KI": 0.06798979450064772, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1102.7765988230706, "W": 104.03, "J_1KI": 6.797989155676951, "W_1KI": 0.6412856535220471, "W_D": 68.81925, "J_D": 729.5228150394558, "W_D_1KI": 0.42423144968900445, "J_D_1KI": 0.00261514507794308} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_052.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_052.output new file mode 100644 index 0000000..d4c7c0b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_052.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 91097, 91097, 91100]), + col_indices=tensor([ 106, 329, 1040, ..., 2232, 16085, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=91100, layout=torch.sparse_csr) +tensor([0.2822, 0.7317, 0.9960, ..., 0.0172, 0.1685, 0.6112]) +Matrix: as-caida_G_052 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 91100 +Density: 9.252097027653536e-05 +Time: 11.029372453689575 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_053.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_053.json new file mode 100644 index 0000000..a5fc97b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_053.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 162739, "MATRIX_FILE": "as-caida_G_053", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90296, "MATRIX_DENSITY": 9.170442955093344e-05, "TIME_S": 10.579174757003784, "TIME_S_1KI": 0.06500700358859146, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1120.1408718323707, "W": 104.23, "J_1KI": 6.883051215949286, "W_1KI": 0.640473396051346, "W_D": 69.08000000000001, "J_D": 742.3902084445955, "W_D_1KI": 0.42448337522044505, "J_D_1KI": 0.0026083690769910413} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_053.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_053.output new file mode 100644 index 0000000..fd55ef0 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_053.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90294, 90294, 90296]), + col_indices=tensor([21783, 106, 329, ..., 160, 16085, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90296, layout=torch.sparse_csr) +tensor([0.7544, 0.0434, 0.8866, ..., 0.4274, 0.5939, 0.3410]) +Matrix: as-caida_G_053 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90296 +Density: 9.170442955093344e-05 +Time: 10.579174757003784 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_054.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_054.json new file mode 100644 index 0000000..452001f --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_054.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 157806, "MATRIX_FILE": "as-caida_G_054", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92170, "MATRIX_DENSITY": 9.360766004816975e-05, "TIME_S": 11.430287837982178, "TIME_S_1KI": 0.07243253005577847, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1116.2398746609688, "W": 103.75, "J_1KI": 7.0734945101008115, "W_1KI": 0.6574528218191957, "W_D": 68.58675, "J_D": 737.9206286593079, "W_D_1KI": 0.4346270103798334, "J_D_1KI": 0.0027541855847042157} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_054.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_054.output new file mode 100644 index 0000000..02816e7 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_054.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 92169, 92169, 92170]), + col_indices=tensor([21783, 106, 329, ..., 155, 160, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92170, layout=torch.sparse_csr) +tensor([0.9821, 0.4383, 0.7062, ..., 0.2709, 0.1073, 0.3932]) +Matrix: as-caida_G_054 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92170 +Density: 9.360766004816975e-05 +Time: 11.430287837982178 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_055.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_055.json new file mode 100644 index 0000000..e5f5f9e --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_055.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 158748, "MATRIX_FILE": "as-caida_G_055", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 91476, "MATRIX_DENSITY": 9.290283509348351e-05, "TIME_S": 10.682826042175293, "TIME_S_1KI": 0.06729424019310663, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1105.6162172555923, "W": 104.53, "J_1KI": 6.964599347743545, "W_1KI": 0.6584649885352887, "W_D": 69.15174999999999, "J_D": 731.4196522682904, "W_D_1KI": 0.4356070627661451, "J_D_1KI": 0.0027440160680206687} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_055.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_055.output new file mode 100644 index 0000000..3b5056d --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_055.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 91475, 91475, 91476]), + col_indices=tensor([21783, 106, 329, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=91476, layout=torch.sparse_csr) +tensor([0.0399, 0.5763, 0.7982, ..., 0.8084, 0.9923, 0.0097]) +Matrix: as-caida_G_055 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 91476 +Density: 9.290283509348351e-05 +Time: 10.682826042175293 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_056.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_056.json new file mode 100644 index 0000000..c289419 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_056.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 154636, "MATRIX_FILE": "as-caida_G_056", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92826, "MATRIX_DENSITY": 9.427389228199419e-05, "TIME_S": 10.989351987838745, "TIME_S_1KI": 0.07106593540856428, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1219.9320558309555, "W": 102.85, "J_1KI": 7.889055949655678, "W_1KI": 0.6651103235986445, "W_D": 67.523, "J_D": 800.9088206696509, "W_D_1KI": 0.43665769937142707, "J_D_1KI": 0.0028237777708387895} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_056.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_056.output new file mode 100644 index 0000000..732dfce --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_056.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 92825, 92825, 92826]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92826, layout=torch.sparse_csr) +tensor([0.5923, 0.0394, 0.2228, ..., 0.2222, 0.2211, 0.9616]) +Matrix: as-caida_G_056 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92826 +Density: 9.427389228199419e-05 +Time: 10.989351987838745 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_057.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_057.json new file mode 100644 index 0000000..caf2487 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_057.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 158516, "MATRIX_FILE": "as-caida_G_057", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92334, "MATRIX_DENSITY": 9.377421810662586e-05, "TIME_S": 10.384201765060425, "TIME_S_1KI": 0.06550885566794787, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1106.9095047950743, "W": 103.6, "J_1KI": 6.982951278073345, "W_1KI": 0.6535617855610789, "W_D": 68.34774999999999, "J_D": 730.2584373200535, "W_D_1KI": 0.4311725630220292, "J_D_1KI": 0.0027200570480079562} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_057.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_057.output new file mode 100644 index 0000000..7e9a08b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_057.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 92333, 92333, 92334]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92334, layout=torch.sparse_csr) +tensor([0.1394, 0.2541, 0.8562, ..., 0.5095, 0.7222, 0.2972]) +Matrix: as-caida_G_057 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92334 +Density: 9.377421810662586e-05 +Time: 10.384201765060425 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_058.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_058.json new file mode 100644 index 0000000..cf8470c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_058.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 157307, "MATRIX_FILE": "as-caida_G_058", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92170, "MATRIX_DENSITY": 9.360766004816975e-05, "TIME_S": 10.229826927185059, "TIME_S_1KI": 0.0650309708225639, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1072.9627659606933, "W": 104.25999999999999, "J_1KI": 6.820820217540817, "W_1KI": 0.6627804229945266, "W_D": 68.97975, "J_D": 709.885894449234, "W_D_1KI": 0.43850400808609913, "J_D_1KI": 0.002787568309649915} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_058.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_058.output new file mode 100644 index 0000000..ece258a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_058.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 92169, 92169, 92170]), + col_indices=tensor([ 996, 25003, 106, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92170, layout=torch.sparse_csr) +tensor([0.7547, 0.0266, 0.9441, ..., 0.1915, 0.6623, 0.5886]) +Matrix: as-caida_G_058 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92170 +Density: 9.360766004816975e-05 +Time: 10.229826927185059 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_059.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_059.json new file mode 100644 index 0000000..d41f172 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_059.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 158003, "MATRIX_FILE": "as-caida_G_059", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93156, "MATRIX_DENSITY": 9.460903959474125e-05, "TIME_S": 10.333704710006714, "TIME_S_1KI": 0.06540195255790532, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1100.3559911084176, "W": 104.33000000000001, "J_1KI": 6.964146194112881, "W_1KI": 0.6603039182800328, "W_D": 68.98675000000001, "J_D": 727.5949743084313, "W_D_1KI": 0.4366167098093075, "J_D_1KI": 0.0027633444289621558} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_059.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_059.output new file mode 100644 index 0000000..e75dd19 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_059.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 93155, 93155, 93156]), + col_indices=tensor([ 996, 25003, 106, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93156, layout=torch.sparse_csr) +tensor([0.8562, 0.3177, 0.9426, ..., 0.6849, 0.9153, 0.6675]) +Matrix: as-caida_G_059 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93156 +Density: 9.460903959474125e-05 +Time: 10.333704710006714 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_060.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_060.json new file mode 100644 index 0000000..56478e2 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_060.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 152831, "MATRIX_FILE": "as-caida_G_060", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94180, "MATRIX_DENSITY": 9.564901186217454e-05, "TIME_S": 10.297740459442139, "TIME_S_1KI": 0.06737991938443208, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1064.9725493431092, "W": 104.4, "J_1KI": 6.968301910889212, "W_1KI": 0.6831074847380441, "W_D": 69.06200000000001, "J_D": 704.49362263155, "W_D_1KI": 0.4518847615994138, "J_D_1KI": 0.002956761138770366} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_060.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_060.output new file mode 100644 index 0000000..b45a637 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_060.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94180, 94180, 94180]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94180, layout=torch.sparse_csr) +tensor([0.8200, 0.1381, 0.1965, ..., 0.3501, 0.2169, 0.2449]) +Matrix: as-caida_G_060 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94180 +Density: 9.564901186217454e-05 +Time: 10.297740459442139 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_061.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_061.json new file mode 100644 index 0000000..dd89464 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_061.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 159024, "MATRIX_FILE": "as-caida_G_061", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94386, "MATRIX_DENSITY": 9.58582250331621e-05, "TIME_S": 10.41711711883545, "TIME_S_1KI": 0.06550657208242434, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1079.3164833664894, "W": 104.03, "J_1KI": 6.787129511058012, "W_1KI": 0.6541779857128484, "W_D": 68.08825, "J_D": 706.4190190193058, "W_D_1KI": 0.42816335898983804, "J_D_1KI": 0.002692444907622988} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_061.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_061.output new file mode 100644 index 0000000..2b1d25b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_061.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94386, 94386, 94386]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94386, layout=torch.sparse_csr) +tensor([0.6025, 0.6851, 0.7546, ..., 0.9123, 0.0632, 0.0882]) +Matrix: as-caida_G_061 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94386 +Density: 9.58582250331621e-05 +Time: 10.41711711883545 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_062.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_062.json new file mode 100644 index 0000000..ae9ee74 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_062.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 160524, "MATRIX_FILE": "as-caida_G_062", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93728, "MATRIX_DENSITY": 9.518996160350281e-05, "TIME_S": 10.325278997421265, "TIME_S_1KI": 0.06432233807668178, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1099.945727186203, "W": 104.44, "J_1KI": 6.852219775150151, "W_1KI": 0.6506192220477934, "W_D": 69.11775, "J_D": 727.937320808351, "W_D_1KI": 0.4305758017492711, "J_D_1KI": 0.002682314181986937} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_062.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_062.output new file mode 100644 index 0000000..eb265e5 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_062.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93728, 93728, 93728]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93728, layout=torch.sparse_csr) +tensor([0.1845, 0.7182, 0.7556, ..., 0.8806, 0.3236, 0.0838]) +Matrix: as-caida_G_062 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93728 +Density: 9.518996160350281e-05 +Time: 10.325278997421265 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_063.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_063.json new file mode 100644 index 0000000..2dab714 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_063.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 155919, "MATRIX_FILE": "as-caida_G_063", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94736, "MATRIX_DENSITY": 9.621368430425745e-05, "TIME_S": 10.676833391189575, "TIME_S_1KI": 0.06847679494602694, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1133.2848464298247, "W": 103.40999999999998, "J_1KI": 7.2684204390088745, "W_1KI": 0.6632289842802993, "W_D": 68.13449999999997, "J_D": 746.6956422886846, "W_D_1KI": 0.4369865122275026, "J_D_1KI": 0.002802650813739843} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_063.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_063.output new file mode 100644 index 0000000..b083a19 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_063.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94736, 94736, 94736]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94736, layout=torch.sparse_csr) +tensor([0.1373, 0.7886, 0.5198, ..., 0.5846, 0.1916, 0.9504]) +Matrix: as-caida_G_063 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94736 +Density: 9.621368430425745e-05 +Time: 10.676833391189575 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_064.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_064.json new file mode 100644 index 0000000..cdc9166 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_064.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 150465, "MATRIX_FILE": "as-caida_G_064", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93558, "MATRIX_DENSITY": 9.50173099575422e-05, "TIME_S": 10.095093011856079, "TIME_S_1KI": 0.06709263291699784, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1036.2830980324745, "W": 103.89, "J_1KI": 6.887203655550955, "W_1KI": 0.6904595753165187, "W_D": 67.99125000000001, "J_D": 678.1998574367167, "W_D_1KI": 0.45187419001096607, "J_D_1KI": 0.003003184727418111} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_064.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_064.output new file mode 100644 index 0000000..a64a4c4 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_064.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93558, 93558, 93558]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93558, layout=torch.sparse_csr) +tensor([0.3072, 0.9205, 0.2129, ..., 0.9134, 0.6202, 0.3911]) +Matrix: as-caida_G_064 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93558 +Density: 9.50173099575422e-05 +Time: 10.095093011856079 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_065.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_065.json new file mode 100644 index 0000000..8659e85 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_065.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 159990, "MATRIX_FILE": "as-caida_G_065", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 95068, "MATRIX_DENSITY": 9.655086281283934e-05, "TIME_S": 10.505874395370483, "TIME_S_1KI": 0.06566581908475831, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1126.470597934723, "W": 104.35000000000001, "J_1KI": 7.04088129217278, "W_1KI": 0.6522282642665167, "W_D": 68.87225000000001, "J_D": 743.484088534832, "W_D_1KI": 0.4304784674042128, "J_D_1KI": 0.002690658587438045} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_065.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_065.output new file mode 100644 index 0000000..a24b056 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_065.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 95068, 95068, 95068]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=95068, layout=torch.sparse_csr) +tensor([0.3887, 0.7020, 0.8359, ..., 0.7487, 0.1236, 0.5776]) +Matrix: as-caida_G_065 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 95068 +Density: 9.655086281283934e-05 +Time: 10.505874395370483 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_066.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_066.json new file mode 100644 index 0000000..28bb975 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_066.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 159458, "MATRIX_FILE": "as-caida_G_066", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93212, "MATRIX_DENSITY": 9.466591307811651e-05, "TIME_S": 10.397132873535156, "TIME_S_1KI": 0.0652029554712536, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1086.220193898678, "W": 104.15000000000002, "J_1KI": 6.81195169824454, "W_1KI": 0.6531500457800802, "W_D": 68.85625000000002, "J_D": 718.1281730785968, "W_D_1KI": 0.4318143335549174, "J_D_1KI": 0.002708012978683524} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_066.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_066.output new file mode 100644 index 0000000..b9a570d --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_066.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93212, 93212, 93212]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93212, layout=torch.sparse_csr) +tensor([0.5806, 0.9067, 0.4889, ..., 0.1534, 0.9816, 0.3873]) +Matrix: as-caida_G_066 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93212 +Density: 9.466591307811651e-05 +Time: 10.397132873535156 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_067.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_067.json new file mode 100644 index 0000000..90ee05f --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_067.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 155289, "MATRIX_FILE": "as-caida_G_067", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94484, "MATRIX_DENSITY": 9.59577536290688e-05, "TIME_S": 10.66397500038147, "TIME_S_1KI": 0.06867179903522766, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1105.1605817985535, "W": 104.24000000000001, "J_1KI": 7.116798883362978, "W_1KI": 0.6712645454603997, "W_D": 68.10775000000001, "J_D": 722.0836590079666, "W_D_1KI": 0.43858708601381946, "J_D_1KI": 0.0028243280980225225} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_067.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_067.output new file mode 100644 index 0000000..15d5cec --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_067.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94484, 94484, 94484]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94484, layout=torch.sparse_csr) +tensor([0.8509, 0.6696, 0.7638, ..., 0.1598, 0.8582, 0.1663]) +Matrix: as-caida_G_067 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94484 +Density: 9.59577536290688e-05 +Time: 10.66397500038147 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_068.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_068.json new file mode 100644 index 0000000..cd2d1f9 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_068.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 157347, "MATRIX_FILE": "as-caida_G_068", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93310, "MATRIX_DENSITY": 9.47654416740232e-05, "TIME_S": 10.728872060775757, "TIME_S_1KI": 0.06818606049543846, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1117.9902378845215, "W": 103.86, "J_1KI": 7.105252962462084, "W_1KI": 0.6600697820740147, "W_D": 68.50625, "J_D": 737.4284492015838, "W_D_1KI": 0.43538326119976867, "J_D_1KI": 0.0027670261345927706} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_068.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_068.output new file mode 100644 index 0000000..761cd9d --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_068.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93310, 93310, 93310]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93310, layout=torch.sparse_csr) +tensor([0.0203, 0.7924, 0.7365, ..., 0.8684, 0.8837, 0.3055]) +Matrix: as-caida_G_068 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93310 +Density: 9.47654416740232e-05 +Time: 10.728872060775757 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_069.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_069.json new file mode 100644 index 0000000..9a2a093 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_069.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 154561, "MATRIX_FILE": "as-caida_G_069", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92190, "MATRIX_DENSITY": 9.362797200651806e-05, "TIME_S": 10.707697629928589, "TIME_S_1KI": 0.06927813374608466, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1106.2047372889517, "W": 103.98999999999998, "J_1KI": 7.15707544134, "W_1KI": 0.6728087939389625, "W_D": 68.59374999999999, "J_D": 729.6733454987406, "W_D_1KI": 0.4437972709803895, "J_D_1KI": 0.002871340577379737} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_069.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_069.output new file mode 100644 index 0000000..c8669d9 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_069.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 92190, 92190, 92190]), + col_indices=tensor([ 106, 329, 1040, ..., 978, 19739, 160]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92190, layout=torch.sparse_csr) +tensor([0.3142, 0.5867, 0.1364, ..., 0.9376, 0.4680, 0.1199]) +Matrix: as-caida_G_069 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92190 +Density: 9.362797200651806e-05 +Time: 10.707697629928589 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_070.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_070.json new file mode 100644 index 0000000..b8e7c0f --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_070.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 168205, "MATRIX_FILE": "as-caida_G_070", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 78684, "MATRIX_DENSITY": 7.991130653390679e-05, "TIME_S": 10.500589609146118, "TIME_S_1KI": 0.06242733336789107, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1050.003953206539, "W": 103.61, "J_1KI": 6.242406309007099, "W_1KI": 0.6159745548586546, "W_D": 67.90350000000001, "J_D": 688.147316249013, "W_D_1KI": 0.4036948961089148, "J_D_1KI": 0.0024000172177338058} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_070.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_070.output new file mode 100644 index 0000000..2c029ab --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_070.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 78684, 78684, 78684]), + col_indices=tensor([ 106, 329, 1040, ..., 16263, 2242, 2242]), + values=tensor([1., 1., 1., ..., 3., 1., 1.]), size=(31379, 31379), + nnz=78684, layout=torch.sparse_csr) +tensor([0.0909, 0.0524, 0.1705, ..., 0.0415, 0.6196, 0.5498]) +Matrix: as-caida_G_070 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 78684 +Density: 7.991130653390679e-05 +Time: 10.500589609146118 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_071.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_071.json new file mode 100644 index 0000000..d2b288c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_071.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 151894, "MATRIX_FILE": "as-caida_G_071", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 96012, "MATRIX_DENSITY": 9.75095872468794e-05, "TIME_S": 10.39712929725647, "TIME_S_1KI": 0.06844990122886006, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1102.9722590446472, "W": 103.8, "J_1KI": 7.261460354224968, "W_1KI": 0.683371298405467, "W_D": 68.00075000000001, "J_D": 722.571684433818, "W_D_1KI": 0.4476855570331943, "J_D_1KI": 0.0029473551097027816} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_071.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_071.output new file mode 100644 index 0000000..a21d4da --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_071.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 96011, 96011, 96012]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=96012, layout=torch.sparse_csr) +tensor([0.5781, 0.8297, 0.6323, ..., 0.9461, 0.8896, 0.2502]) +Matrix: as-caida_G_071 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 96012 +Density: 9.75095872468794e-05 +Time: 10.39712929725647 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_072.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_072.json new file mode 100644 index 0000000..bd049b8 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_072.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 151068, "MATRIX_FILE": "as-caida_G_072", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 96404, "MATRIX_DENSITY": 9.79077016305062e-05, "TIME_S": 10.206506252288818, "TIME_S_1KI": 0.06756233121699379, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1078.23351252079, "W": 104.3, "J_1KI": 7.137405092546337, "W_1KI": 0.6904175603039691, "W_D": 69.00175, "J_D": 713.3269345405698, "W_D_1KI": 0.45675953875076125, "J_D_1KI": 0.00302353601524321} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_072.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_072.output new file mode 100644 index 0000000..f81392c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_072.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 96403, 96403, 96404]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=96404, layout=torch.sparse_csr) +tensor([0.5234, 0.1945, 0.1424, ..., 0.1285, 0.2891, 0.1248]) +Matrix: as-caida_G_072 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 96404 +Density: 9.79077016305062e-05 +Time: 10.206506252288818 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_073.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_073.json new file mode 100644 index 0000000..33e86da --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_073.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 134499, "MATRIX_FILE": "as-caida_G_073", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 95554, "MATRIX_DENSITY": 9.704444340070319e-05, "TIME_S": 12.881189823150635, "TIME_S_1KI": 0.09577164010996837, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 2676.0662737393377, "W": 98.33, "J_1KI": 19.896551451976134, "W_1KI": 0.7310835024795723, "W_D": 54.637249999999995, "J_D": 1486.9612734146713, "W_D_1KI": 0.4062279273451847, "J_D_1KI": 0.0030203044434916593} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_073.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_073.output new file mode 100644 index 0000000..f96548f --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_073.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 95553, 95553, 95554]), + col_indices=tensor([22754, 22754, 106, ..., 978, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=95554, layout=torch.sparse_csr) +tensor([0.4158, 0.5267, 0.6796, ..., 0.6624, 0.8810, 0.3678]) +Matrix: as-caida_G_073 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 95554 +Density: 9.704444340070319e-05 +Time: 12.881189823150635 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_074.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_074.json new file mode 100644 index 0000000..528c6ba --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_074.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 149784, "MATRIX_FILE": "as-caida_G_074", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 97296, "MATRIX_DENSITY": 9.881361497284067e-05, "TIME_S": 10.186426162719727, "TIME_S_1KI": 0.06800743846285136, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1090.3021710205078, "W": 103.67999999999999, "J_1KI": 7.279163135051192, "W_1KI": 0.6921967633392084, "W_D": 68.15949999999998, "J_D": 716.7674655253885, "W_D_1KI": 0.4550519414623724, "J_D_1KI": 0.0030380544080968086} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_074.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_074.output new file mode 100644 index 0000000..5a49bea --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_074.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 97295, 97295, 97296]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=97296, layout=torch.sparse_csr) +tensor([0.8665, 0.9114, 0.0727, ..., 0.9185, 0.7834, 0.7294]) +Matrix: as-caida_G_074 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 97296 +Density: 9.881361497284067e-05 +Time: 10.186426162719727 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_075.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_075.json new file mode 100644 index 0000000..53c0688 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_075.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 159620, "MATRIX_FILE": "as-caida_G_075", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 97492, "MATRIX_DENSITY": 9.901267216465406e-05, "TIME_S": 10.568409204483032, "TIME_S_1KI": 0.06620980581683393, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1173.7224353432655, "W": 103.85, "J_1KI": 7.353229140103154, "W_1KI": 0.6506076932715198, "W_D": 68.54724999999999, "J_D": 774.7274454124569, "W_D_1KI": 0.42944023305350204, "J_D_1KI": 0.0026903911355312744} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_075.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_075.output new file mode 100644 index 0000000..7210413 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_075.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 97491, 97491, 97492]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=97492, layout=torch.sparse_csr) +tensor([0.5496, 0.6182, 0.9131, ..., 0.3808, 0.2966, 0.4374]) +Matrix: as-caida_G_075 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 97492 +Density: 9.901267216465406e-05 +Time: 10.568409204483032 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_076.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_076.json new file mode 100644 index 0000000..c14734e --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_076.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 154766, "MATRIX_FILE": "as-caida_G_076", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98178, "MATRIX_DENSITY": 9.970937233600097e-05, "TIME_S": 10.274536371231079, "TIME_S_1KI": 0.06638755522033961, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1116.240790901184, "W": 104.57, "J_1KI": 7.212441950436039, "W_1KI": 0.6756651977824586, "W_D": 62.394749999999995, "J_D": 666.0377267675399, "W_D_1KI": 0.40315540881072065, "J_D_1KI": 0.002604935249413441} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_076.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_076.output new file mode 100644 index 0000000..ae39f55 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_076.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98177, 98177, 98178]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98178, layout=torch.sparse_csr) +tensor([0.6988, 0.8981, 0.7500, ..., 0.6179, 0.7642, 0.2168]) +Matrix: as-caida_G_076 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98178 +Density: 9.970937233600097e-05 +Time: 10.274536371231079 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_077.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_077.json new file mode 100644 index 0000000..7c72eb2 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_077.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 165221, "MATRIX_FILE": "as-caida_G_077", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98664, "MATRIX_DENSITY": 0.00010020295292386482, "TIME_S": 10.493607997894287, "TIME_S_1KI": 0.06351255589721819, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1101.9741387581826, "W": 105.11, "J_1KI": 6.6696977911898765, "W_1KI": 0.6361782097917336, "W_D": 69.27000000000001, "J_D": 726.2272723031045, "W_D_1KI": 0.4192566320261953, "J_D_1KI": 0.00253755050523962} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_077.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_077.output new file mode 100644 index 0000000..1d9559e --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_077.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98663, 98663, 98664]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98664, layout=torch.sparse_csr) +tensor([0.3477, 0.7522, 0.6764, ..., 0.6680, 0.5085, 0.7475]) +Matrix: as-caida_G_077 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98664 +Density: 0.00010020295292386482 +Time: 10.493607997894287 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_078.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_078.json new file mode 100644 index 0000000..6d006fe --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_078.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 161235, "MATRIX_FILE": "as-caida_G_078", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98782, "MATRIX_DENSITY": 0.00010032279347811982, "TIME_S": 10.226710081100464, "TIME_S_1KI": 0.0634273580866466, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1150.7420145750045, "W": 104.1, "J_1KI": 7.137048497999842, "W_1KI": 0.6456414550190716, "W_D": 68.95224999999999, "J_D": 762.2118258835673, "W_D_1KI": 0.4276506341675194, "J_D_1KI": 0.0026523436857228233} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_078.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_078.output new file mode 100644 index 0000000..50579bc --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_078.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98781, 98781, 98782]), + col_indices=tensor([22754, 22754, 106, ..., 4133, 31329, 12170]), + values=tensor([1., 1., 1., ..., 3., 3., 1.]), size=(31379, 31379), + nnz=98782, layout=torch.sparse_csr) +tensor([0.5060, 0.1883, 0.1585, ..., 0.1666, 0.6708, 0.7561]) +Matrix: as-caida_G_078 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98782 +Density: 0.00010032279347811982 +Time: 10.226710081100464 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_079.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_079.json new file mode 100644 index 0000000..62c6764 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_079.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 164465, "MATRIX_FILE": "as-caida_G_079", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98392, "MATRIX_DENSITY": 9.992671029032785e-05, "TIME_S": 11.05835509300232, "TIME_S_1KI": 0.06723834915028924, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1113.1310436725616, "W": 104.57, "J_1KI": 6.768194106177981, "W_1KI": 0.6358191712522421, "W_D": 69.29249999999999, "J_D": 737.607658445835, "W_D_1KI": 0.4213206457300945, "J_D_1KI": 0.0025617647872197393} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_079.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_079.output new file mode 100644 index 0000000..ed78fdb --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_079.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 98391, 98391, 98392]), + col_indices=tensor([22754, 106, 329, ..., 4133, 31329, 12170]), + values=tensor([1., 1., 1., ..., 3., 3., 1.]), size=(31379, 31379), + nnz=98392, layout=torch.sparse_csr) +tensor([0.7991, 0.8675, 0.4304, ..., 0.9364, 0.1142, 0.0836]) +Matrix: as-caida_G_079 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98392 +Density: 9.992671029032785e-05 +Time: 11.05835509300232 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_080.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_080.json new file mode 100644 index 0000000..8cb45fd --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_080.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 148685, "MATRIX_FILE": "as-caida_G_080", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98112, "MATRIX_DENSITY": 9.964234287345156e-05, "TIME_S": 10.231786727905273, "TIME_S_1KI": 0.06881519136365655, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1049.2246556282043, "W": 104.2, "J_1KI": 7.056694727969899, "W_1KI": 0.7008104381746646, "W_D": 68.26025, "J_D": 687.3352907806635, "W_D_1KI": 0.4590930490634563, "J_D_1KI": 0.0030876890679184606} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_080.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_080.output new file mode 100644 index 0000000..ef63008 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_080.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98111, 98111, 98112]), + col_indices=tensor([22754, 22754, 106, ..., 4133, 31329, 12170]), + values=tensor([1., 1., 1., ..., 3., 3., 1.]), size=(31379, 31379), + nnz=98112, layout=torch.sparse_csr) +tensor([0.9695, 0.5610, 0.7110, ..., 0.0948, 0.5347, 0.9791]) +Matrix: as-caida_G_080 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98112 +Density: 9.964234287345156e-05 +Time: 10.231786727905273 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_081.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_081.json new file mode 100644 index 0000000..613d5bb --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_081.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 159450, "MATRIX_FILE": "as-caida_G_081", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85988, "MATRIX_DENSITY": 8.732923372270826e-05, "TIME_S": 10.923879146575928, "TIME_S_1KI": 0.06850974692114098, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1061.8722890520096, "W": 103.39, "J_1KI": 6.659594161505234, "W_1KI": 0.6484164314832236, "W_D": 68.07575, "J_D": 699.1754761720896, "W_D_1KI": 0.4269410473502665, "J_D_1KI": 0.0026775857469442865} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_081.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_081.output new file mode 100644 index 0000000..9c583d7 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_081.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 85987, 85987, 85988]), + col_indices=tensor([22754, 106, 329, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=85988, layout=torch.sparse_csr) +tensor([0.1300, 0.1233, 0.4399, ..., 0.9028, 0.5293, 0.6499]) +Matrix: as-caida_G_081 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85988 +Density: 8.732923372270826e-05 +Time: 10.923879146575928 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_082.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_082.json new file mode 100644 index 0000000..c86b5b3 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_082.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 163540, "MATRIX_FILE": "as-caida_G_082", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98400, "MATRIX_DENSITY": 9.993483507366717e-05, "TIME_S": 11.202447652816772, "TIME_S_1KI": 0.06849974105917067, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1130.0558170413972, "W": 104.84, "J_1KI": 6.909965861816052, "W_1KI": 0.6410664057722882, "W_D": 69.577, "J_D": 749.9608315746784, "W_D_1KI": 0.4254433166197872, "J_D_1KI": 0.00260146335220611} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_082.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_082.output new file mode 100644 index 0000000..ce6b5c4 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_082.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 98399, 98399, 98400]), + col_indices=tensor([22754, 106, 329, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98400, layout=torch.sparse_csr) +tensor([0.5867, 0.4111, 0.8491, ..., 0.5237, 0.9809, 0.4170]) +Matrix: as-caida_G_082 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98400 +Density: 9.993483507366717e-05 +Time: 11.202447652816772 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_083.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_083.json new file mode 100644 index 0000000..7bc6ec3 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_083.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 166715, "MATRIX_FILE": "as-caida_G_083", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98450, "MATRIX_DENSITY": 9.998561496953794e-05, "TIME_S": 11.187878608703613, "TIME_S_1KI": 0.06710781038720938, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1097.3230828523635, "W": 105.22999999999999, "J_1KI": 6.582029708498717, "W_1KI": 0.6311969528836637, "W_D": 69.88449999999999, "J_D": 728.7453671348094, "W_D_1KI": 0.41918543622349513, "J_D_1KI": 0.00251438344614159} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_083.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_083.output new file mode 100644 index 0000000..99156e5 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_083.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98449, 98449, 98450]), + col_indices=tensor([22754, 22754, 106, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98450, layout=torch.sparse_csr) +tensor([0.0625, 0.0207, 0.6103, ..., 0.9181, 0.6597, 0.5274]) +Matrix: as-caida_G_083 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98450 +Density: 9.998561496953794e-05 +Time: 11.187878608703613 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_084.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_084.json new file mode 100644 index 0000000..7ca42ac --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_084.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 154819, "MATRIX_FILE": "as-caida_G_084", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 97972, "MATRIX_DENSITY": 9.950015916501341e-05, "TIME_S": 11.054297685623169, "TIME_S_1KI": 0.07140142802642549, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1151.5412223386763, "W": 104.02, "J_1KI": 7.437983854298738, "W_1KI": 0.6718813582312247, "W_D": 68.81375, "J_D": 761.7945567074418, "W_D_1KI": 0.44447871385295085, "J_D_1KI": 0.0028709571425532448} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_084.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_084.output new file mode 100644 index 0000000..8ca958a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_084.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 97971, 97971, 97972]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=97972, layout=torch.sparse_csr) +tensor([0.9735, 0.5472, 0.1634, ..., 0.2538, 0.0294, 0.6590]) +Matrix: as-caida_G_084 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 97972 +Density: 9.950015916501341e-05 +Time: 11.054297685623169 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_085.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_085.json new file mode 100644 index 0000000..52ec92b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_085.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 161944, "MATRIX_FILE": "as-caida_G_085", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99166, "MATRIX_DENSITY": 0.0001007127830784073, "TIME_S": 10.508598566055298, "TIME_S_1KI": 0.06489032360603232, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1094.9015096378328, "W": 104.89000000000001, "J_1KI": 6.760988425862229, "W_1KI": 0.6476930296892754, "W_D": 69.60000000000002, "J_D": 726.5244071960451, "W_D_1KI": 0.4297781949315814, "J_D_1KI": 0.002653869207451844} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_085.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_085.output new file mode 100644 index 0000000..f5d07d3 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_085.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99165, 99165, 99166]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99166, layout=torch.sparse_csr) +tensor([0.3020, 0.1618, 0.1209, ..., 0.5325, 0.8315, 0.5921]) +Matrix: as-caida_G_085 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99166 +Density: 0.0001007127830784073 +Time: 10.508598566055298 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_086.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_086.json new file mode 100644 index 0000000..34b2797 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_086.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 161492, "MATRIX_FILE": "as-caida_G_086", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99660, "MATRIX_DENSITY": 0.00010121448844961047, "TIME_S": 10.289419651031494, "TIME_S_1KI": 0.06371473293433418, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1085.6768887281419, "W": 105.15, "J_1KI": 6.722790532832226, "W_1KI": 0.6511158447477274, "W_D": 69.20750000000001, "J_D": 714.5695033442975, "W_D_1KI": 0.4285506402793947, "J_D_1KI": 0.002653695788518284} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_086.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_086.output new file mode 100644 index 0000000..54d7cd9 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_086.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99659, 99659, 99660]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99660, layout=torch.sparse_csr) +tensor([0.7948, 0.9702, 0.9353, ..., 0.9050, 0.1404, 0.0479]) +Matrix: as-caida_G_086 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99660 +Density: 0.00010121448844961047 +Time: 10.289419651031494 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_087.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_087.json new file mode 100644 index 0000000..a4c79ae --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_087.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 153392, "MATRIX_FILE": "as-caida_G_087", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99652, "MATRIX_DENSITY": 0.00010120636366627115, "TIME_S": 10.110106945037842, "TIME_S_1KI": 0.0659102622368692, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1042.078316512108, "W": 104.54, "J_1KI": 6.7935636572448885, "W_1KI": 0.6815218525086054, "W_D": 68.75475, "J_D": 685.3628671533465, "W_D_1KI": 0.4482290471471785, "J_D_1KI": 0.0029221148896107912} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_087.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_087.output new file mode 100644 index 0000000..f18de79 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_087.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99651, 99651, 99652]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99652, layout=torch.sparse_csr) +tensor([0.7897, 0.3093, 0.8302, ..., 0.1367, 0.6743, 0.3840]) +Matrix: as-caida_G_087 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99652 +Density: 0.00010120636366627115 +Time: 10.110106945037842 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_088.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_088.json new file mode 100644 index 0000000..4a97f90 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_088.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 158942, "MATRIX_FILE": "as-caida_G_088", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 100366, "MATRIX_DENSITY": 0.00010193150057930568, "TIME_S": 10.011077642440796, "TIME_S_1KI": 0.06298572839426203, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1114.832428407669, "W": 104.46000000000001, "J_1KI": 7.014083303391609, "W_1KI": 0.6572208730228638, "W_D": 69.13950000000001, "J_D": 737.8801137650014, "W_D_1KI": 0.43499830126712896, "J_D_1KI": 0.0027368367157021363} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_088.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_088.output new file mode 100644 index 0000000..c819ff5 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_088.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 100365, 100365, + 100366]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=100366, layout=torch.sparse_csr) +tensor([0.1812, 0.6581, 0.8089, ..., 0.1241, 0.1488, 0.6882]) +Matrix: as-caida_G_088 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 100366 +Density: 0.00010193150057930568 +Time: 10.011077642440796 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_089.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_089.json new file mode 100644 index 0000000..164be68 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_089.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 160895, "MATRIX_FILE": "as-caida_G_089", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 101476, "MATRIX_DENSITY": 0.00010305881426763669, "TIME_S": 10.658544540405273, "TIME_S_1KI": 0.06624534348740031, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1118.6940277862548, "W": 104.88, "J_1KI": 6.952944639586406, "W_1KI": 0.6518536934025296, "W_D": 69.62525, "J_D": 742.6520915153026, "W_D_1KI": 0.432737188849871, "J_D_1KI": 0.0026895626890199886} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_089.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_089.output new file mode 100644 index 0000000..7af1f6a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_089.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 101475, 101475, + 101476]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=101476, layout=torch.sparse_csr) +tensor([0.3322, 0.6196, 0.6346, ..., 0.4619, 0.0025, 0.4685]) +Matrix: as-caida_G_089 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 101476 +Density: 0.00010305881426763669 +Time: 10.658544540405273 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_090.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_090.json new file mode 100644 index 0000000..bd84a3c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_090.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 156059, "MATRIX_FILE": "as-caida_G_090", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 100924, "MATRIX_DENSITY": 0.00010249820421722343, "TIME_S": 10.132919073104858, "TIME_S_1KI": 0.06493005256412548, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1072.1474975681303, "W": 104.45999999999998, "J_1KI": 6.870142046073154, "W_1KI": 0.6693622283879813, "W_D": 69.10899999999998, "J_D": 709.3149665846822, "W_D_1KI": 0.4428389263035133, "J_D_1KI": 0.002837637856858709} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_090.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_090.output new file mode 100644 index 0000000..2e320fd --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_090.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 100923, 100923, + 100924]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=100924, layout=torch.sparse_csr) +tensor([0.0061, 0.6955, 0.4001, ..., 0.3121, 0.2448, 0.5232]) +Matrix: as-caida_G_090 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 100924 +Density: 0.00010249820421722343 +Time: 10.132919073104858 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_091.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_091.json new file mode 100644 index 0000000..6885f01 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_091.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 163972, "MATRIX_FILE": "as-caida_G_091", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 101654, "MATRIX_DENSITY": 0.00010323959069693661, "TIME_S": 10.949605226516724, "TIME_S_1KI": 0.06677728652767986, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1139.361243982315, "W": 105.01, "J_1KI": 6.948510989573312, "W_1KI": 0.6404142170614495, "W_D": 69.73250000000002, "J_D": 756.5994471573831, "W_D_1KI": 0.4252707779376968, "J_D_1KI": 0.0025935573020863124} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_091.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_091.output new file mode 100644 index 0000000..fddd600 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_091.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 101653, 101653, + 101654]), + col_indices=tensor([ 106, 329, 1040, ..., 19739, 155, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=101654, layout=torch.sparse_csr) +tensor([0.8384, 0.2439, 0.2433, ..., 0.6668, 0.6423, 0.8572]) +Matrix: as-caida_G_091 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 101654 +Density: 0.00010323959069693661 +Time: 10.949605226516724 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_092.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_092.json new file mode 100644 index 0000000..b062e07 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_092.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 164547, "MATRIX_FILE": "as-caida_G_092", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 101762, "MATRIX_DENSITY": 0.00010334927527201746, "TIME_S": 10.835957527160645, "TIME_S_1KI": 0.06585326701283307, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1173.0413549804687, "W": 105.32, "J_1KI": 7.1289136537309625, "W_1KI": 0.6400602867265887, "W_D": 70.02924999999999, "J_D": 779.977272201538, "W_D_1KI": 0.4255881298352446, "J_D_1KI": 0.0025864229055239207} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_092.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_092.output new file mode 100644 index 0000000..41df9ee --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_092.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 101761, 101761, + 101762]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=101762, layout=torch.sparse_csr) +tensor([0.2109, 0.0917, 0.8371, ..., 0.2332, 0.4506, 0.6001]) +Matrix: as-caida_G_092 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 101762 +Density: 0.00010334927527201746 +Time: 10.835957527160645 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_093.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_093.json new file mode 100644 index 0000000..756cf82 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_093.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 166681, "MATRIX_FILE": "as-caida_G_093", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99916, "MATRIX_DENSITY": 0.0001014744815164688, "TIME_S": 10.825764179229736, "TIME_S_1KI": 0.06494899946142473, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1155.7523360443115, "W": 105.28, "J_1KI": 6.933917699343725, "W_1KI": 0.6316256801915036, "W_D": 69.9205, "J_D": 767.579608780265, "W_D_1KI": 0.4194869241245253, "J_D_1KI": 0.002516705108107855} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_093.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_093.output new file mode 100644 index 0000000..0597309 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_093.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99914, 99915, 99916]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99916, layout=torch.sparse_csr) +tensor([0.7707, 0.4963, 0.6598, ..., 0.9680, 0.9161, 0.2747]) +Matrix: as-caida_G_093 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99916 +Density: 0.0001014744815164688 +Time: 10.825764179229736 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_094.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_094.json new file mode 100644 index 0000000..59dc071 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_094.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 159545, "MATRIX_FILE": "as-caida_G_094", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102476, "MATRIX_DENSITY": 0.000104074412185052, "TIME_S": 10.30429983139038, "TIME_S_1KI": 0.06458553907292852, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1117.1915744304658, "W": 105.15000000000002, "J_1KI": 7.002360302300078, "W_1KI": 0.6590617067285093, "W_D": 69.82750000000001, "J_D": 741.899140880108, "W_D_1KI": 0.43766648907831657, "J_D_1KI": 0.0027432165788856848} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_094.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_094.output new file mode 100644 index 0000000..5dd8f9b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_094.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102474, 102475, + 102476]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102476, layout=torch.sparse_csr) +tensor([0.2754, 0.2780, 0.7138, ..., 0.0844, 0.6533, 0.6431]) +Matrix: as-caida_G_094 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102476 +Density: 0.000104074412185052 +Time: 10.30429983139038 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_095.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_095.json new file mode 100644 index 0000000..eaca5cf --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_095.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 166826, "MATRIX_FILE": "as-caida_G_095", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102290, "MATRIX_DENSITY": 0.00010388551097241275, "TIME_S": 11.026093482971191, "TIME_S_1KI": 0.06609337563072418, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1149.8133525252342, "W": 106.35, "J_1KI": 6.892291084874266, "W_1KI": 0.6374905590255715, "W_D": 70.8265, "J_D": 765.747582629323, "W_D_1KI": 0.42455312721038685, "J_D_1KI": 0.0025448858523874386} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_095.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_095.output new file mode 100644 index 0000000..160a9d2 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_095.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102289, 102289, + 102290]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 25970, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102290, layout=torch.sparse_csr) +tensor([0.4348, 0.4670, 0.5984, ..., 0.7837, 0.3098, 0.9887]) +Matrix: as-caida_G_095 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102290 +Density: 0.00010388551097241275 +Time: 11.026093482971191 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_096.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_096.json new file mode 100644 index 0000000..1d5e239 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_096.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 162500, "MATRIX_FILE": "as-caida_G_096", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102356, "MATRIX_DENSITY": 0.00010395254043496216, "TIME_S": 10.665158987045288, "TIME_S_1KI": 0.06563174761258639, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1167.590767211914, "W": 104.66, "J_1KI": 7.185173952073317, "W_1KI": 0.6440615384615384, "W_D": 69.515, "J_D": 775.5118687438965, "W_D_1KI": 0.4277846153846154, "J_D_1KI": 0.0026325207100591714} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_096.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_096.output new file mode 100644 index 0000000..6e088f9 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_096.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102354, 102355, + 102356]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102356, layout=torch.sparse_csr) +tensor([0.6829, 0.5557, 0.6218, ..., 0.6117, 0.5711, 0.7363]) +Matrix: as-caida_G_096 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102356 +Density: 0.00010395254043496216 +Time: 10.665158987045288 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_097.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_097.json new file mode 100644 index 0000000..c4c17f3 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_097.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 160170, "MATRIX_FILE": "as-caida_G_097", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102212, "MATRIX_DENSITY": 0.00010380629433485436, "TIME_S": 10.591028928756714, "TIME_S_1KI": 0.06612367440067873, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1170.05947807312, "W": 104.67999999999999, "J_1KI": 7.305110058519824, "W_1KI": 0.6535555971779984, "W_D": 69.38499999999999, "J_D": 775.5500275707244, "W_D_1KI": 0.4331959792720234, "J_D_1KI": 0.002704601231641527} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_097.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_097.output new file mode 100644 index 0000000..8c4711c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_097.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102210, 102211, + 102212]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102212, layout=torch.sparse_csr) +tensor([0.1517, 0.0211, 0.0448, ..., 0.1200, 0.2979, 0.2233]) +Matrix: as-caida_G_097 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102212 +Density: 0.00010380629433485436 +Time: 10.591028928756714 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_098.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_098.json new file mode 100644 index 0000000..43fc893 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_098.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 151021, "MATRIX_FILE": "as-caida_G_098", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102468, "MATRIX_DENSITY": 0.00010406628740171267, "TIME_S": 10.2952299118042, "TIME_S_1KI": 0.06817084982753524, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1059.097394413948, "W": 104.46, "J_1KI": 7.012914723210335, "W_1KI": 0.6916918839101847, "W_D": 69.02574999999999, "J_D": 699.8371814327835, "W_D_1KI": 0.4570606074651869, "J_D_1KI": 0.003026470540290336} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_098.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_098.output new file mode 100644 index 0000000..a905ba8 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_098.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102466, 102467, + 102468]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102468, layout=torch.sparse_csr) +tensor([0.8043, 0.1229, 0.0900, ..., 0.6126, 0.6807, 0.1960]) +Matrix: as-caida_G_098 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102468 +Density: 0.00010406628740171267 +Time: 10.2952299118042 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_099.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_099.json new file mode 100644 index 0000000..057a88a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_099.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 162222, "MATRIX_FILE": "as-caida_G_099", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 103510, "MATRIX_DENSITY": 0.00010512454043165944, "TIME_S": 10.81563925743103, "TIME_S_1KI": 0.06667184017846549, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1431.2589439249039, "W": 106.09, "J_1KI": 8.822841192470218, "W_1KI": 0.6539803479182849, "W_D": 69.94975, "J_D": 943.6912556585073, "W_D_1KI": 0.4311976797228489, "J_D_1KI": 0.0026580715298963695} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_099.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_099.output new file mode 100644 index 0000000..9116958 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_099.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 103508, 103509, + 103510]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=103510, layout=torch.sparse_csr) +tensor([0.2735, 0.8903, 0.8909, ..., 0.2047, 0.9165, 0.1154]) +Matrix: as-caida_G_099 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 103510 +Density: 0.00010512454043165944 +Time: 10.81563925743103 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_100.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_100.json new file mode 100644 index 0000000..4612ffc --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_100.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 161861, "MATRIX_FILE": "as-caida_G_100", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102888, "MATRIX_DENSITY": 0.00010449283852702711, "TIME_S": 10.643919706344604, "TIME_S_1KI": 0.06575963145133544, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1085.8985073637962, "W": 105.49, "J_1KI": 6.708833550786145, "W_1KI": 0.651732041690092, "W_D": 70.16424999999998, "J_D": 722.2604450213311, "W_D_1KI": 0.43348459480665497, "J_D_1KI": 0.0026781287327191537} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_100.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_100.output new file mode 100644 index 0000000..a36ebd6 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_100.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102886, 102887, + 102888]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102888, layout=torch.sparse_csr) +tensor([0.5701, 0.7395, 0.7226, ..., 0.4098, 0.4760, 0.8418]) +Matrix: as-caida_G_100 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102888 +Density: 0.00010449283852702711 +Time: 10.643919706344604 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_101.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_101.json new file mode 100644 index 0000000..b3cf760 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_101.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 156858, "MATRIX_FILE": "as-caida_G_101", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 103020, "MATRIX_DENSITY": 0.00010462689745212593, "TIME_S": 10.364076137542725, "TIME_S_1KI": 0.06607298408460342, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1055.4887836170196, "W": 104.67999999999999, "J_1KI": 6.728944546131021, "W_1KI": 0.6673551874944217, "W_D": 68.84349999999999, "J_D": 694.1492364820241, "W_D_1KI": 0.4388905889403154, "J_D_1KI": 0.002798012144361878} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_101.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_101.output new file mode 100644 index 0000000..89ecebb --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_101.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 103017, 103018, + 103020]), + col_indices=tensor([ 106, 329, 1040, ..., 5128, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=103020, layout=torch.sparse_csr) +tensor([0.0606, 0.9100, 0.6597, ..., 0.6766, 0.5325, 0.8565]) +Matrix: as-caida_G_101 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 103020 +Density: 0.00010462689745212593 +Time: 10.364076137542725 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_102.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_102.json new file mode 100644 index 0000000..bbddd68 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_102.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 154089, "MATRIX_FILE": "as-caida_G_102", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104096, "MATRIX_DENSITY": 0.00010571968081126482, "TIME_S": 10.577264547348022, "TIME_S_1KI": 0.06864386521651787, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1058.5693076252937, "W": 104.99, "J_1KI": 6.869856431187779, "W_1KI": 0.6813594740701803, "W_D": 69.5315, "J_D": 701.0564035922288, "W_D_1KI": 0.4512424637709375, "J_D_1KI": 0.0029284534507391024} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_102.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_102.output new file mode 100644 index 0000000..7f83f2f --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_102.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104094, 104094, + 104096]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104096, layout=torch.sparse_csr) +tensor([0.6843, 0.0947, 0.1401, ..., 0.3123, 0.9688, 0.9031]) +Matrix: as-caida_G_102 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104096 +Density: 0.00010571968081126482 +Time: 10.577264547348022 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_103.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_103.json new file mode 100644 index 0000000..d19b339 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_103.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 160384, "MATRIX_FILE": "as-caida_G_103", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104634, "MATRIX_DENSITY": 0.00010626607249083426, "TIME_S": 10.527945518493652, "TIME_S_1KI": 0.06564211840640995, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1124.1111827135085, "W": 105.35, "J_1KI": 7.008873595330634, "W_1KI": 0.656861033519553, "W_D": 70.2345, "J_D": 749.419903771162, "W_D_1KI": 0.4379146298882681, "J_D_1KI": 0.0027304134445347923} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_103.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_103.output new file mode 100644 index 0000000..4a35610 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_103.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104632, 104632, + 104634]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104634, layout=torch.sparse_csr) +tensor([0.8633, 0.3410, 0.6610, ..., 0.1230, 0.6186, 0.6358]) +Matrix: as-caida_G_103 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104634 +Density: 0.00010626607249083426 +Time: 10.527945518493652 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_104.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_104.json new file mode 100644 index 0000000..e638e3c --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_104.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 155714, "MATRIX_FILE": "as-caida_G_104", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104824, "MATRIX_DENSITY": 0.00010645903609514317, "TIME_S": 10.597099781036377, "TIME_S_1KI": 0.06805489410737876, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1089.0991630220412, "W": 104.41999999999999, "J_1KI": 6.994227641843644, "W_1KI": 0.670588386400709, "W_D": 69.06174999999999, "J_D": 720.3131021053194, "W_D_1KI": 0.44351663948007236, "J_D_1KI": 0.002848277222857754} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_104.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_104.output new file mode 100644 index 0000000..a77e063 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_104.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104823, 104823, + 104824]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104824, layout=torch.sparse_csr) +tensor([0.9344, 0.9356, 0.3992, ..., 0.2312, 0.5790, 0.2517]) +Matrix: as-caida_G_104 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104824 +Density: 0.00010645903609514317 +Time: 10.597099781036377 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_105.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_105.json new file mode 100644 index 0000000..14b25e3 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_105.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 162524, "MATRIX_FILE": "as-caida_G_105", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104726, "MATRIX_DENSITY": 0.00010635950749923647, "TIME_S": 10.825753450393677, "TIME_S_1KI": 0.06661018342148653, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1140.3835336875916, "W": 105.82000000000001, "J_1KI": 7.016708508820799, "W_1KI": 0.6511038369717704, "W_D": 70.57150000000001, "J_D": 760.523308898449, "W_D_1KI": 0.4342220225935863, "J_D_1KI": 0.002671740928069616} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_105.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_105.output new file mode 100644 index 0000000..10d6bc2 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_105.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104725, 104725, + 104726]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104726, layout=torch.sparse_csr) +tensor([0.4643, 0.2679, 0.2663, ..., 0.2417, 0.4911, 0.3960]) +Matrix: as-caida_G_105 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104726 +Density: 0.00010635950749923647 +Time: 10.825753450393677 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_106.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_106.json new file mode 100644 index 0000000..e8026b3 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_106.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 160426, "MATRIX_FILE": "as-caida_G_106", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105092, "MATRIX_DENSITY": 0.00010673121633701047, "TIME_S": 11.117560863494873, "TIME_S_1KI": 0.06930024349852812, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1141.4218996024133, "W": 104.73000000000002, "J_1KI": 7.114943335883294, "W_1KI": 0.6528243551544015, "W_D": 69.66675000000002, "J_D": 759.2777057588698, "W_D_1KI": 0.43426096767356925, "J_D_1KI": 0.002706923863174107} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_106.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_106.output new file mode 100644 index 0000000..4777dac --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_106.output @@ -0,0 +1,16 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105091, 105091, + 105092]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105092, layout=torch.sparse_csr) +tensor([4.1192e-01, 7.3228e-01, 8.8503e-01, ..., 9.1324e-01, 1.6916e-04, + 2.2430e-01]) +Matrix: as-caida_G_106 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105092 +Density: 0.00010673121633701047 +Time: 11.117560863494873 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_107.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_107.json new file mode 100644 index 0000000..e23515a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_107.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 156844, "MATRIX_FILE": "as-caida_G_107", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105332, "MATRIX_DENSITY": 0.00010697495983719015, "TIME_S": 10.442288875579834, "TIME_S_1KI": 0.06657754759875949, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1075.521778292656, "W": 105.54000000000002, "J_1KI": 6.85727078047395, "W_1KI": 0.6728979113004004, "W_D": 70.30450000000002, "J_D": 716.4489374831917, "W_D_1KI": 0.4482447527479535, "J_D_1KI": 0.0028579018180354587} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_107.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_107.output new file mode 100644 index 0000000..748291b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_107.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105330, 105330, + 105332]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105332, layout=torch.sparse_csr) +tensor([0.9773, 0.5550, 0.4404, ..., 0.9777, 0.1935, 0.0053]) +Matrix: as-caida_G_107 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105332 +Density: 0.00010697495983719015 +Time: 10.442288875579834 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_108.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_108.json new file mode 100644 index 0000000..938964f --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_108.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 157767, "MATRIX_FILE": "as-caida_G_108", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105524, "MATRIX_DENSITY": 0.0001071699546373339, "TIME_S": 10.835067510604858, "TIME_S_1KI": 0.06867765445628592, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1090.171316576004, "W": 105.4, "J_1KI": 6.910008535219685, "W_1KI": 0.6680738050416121, "W_D": 70.15775000000001, "J_D": 725.654332879603, "W_D_1KI": 0.4446921726343279, "J_D_1KI": 0.0028186640592413365} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_108.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_108.output new file mode 100644 index 0000000..6a10aa7 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_108.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105522, 105522, + 105524]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105524, layout=torch.sparse_csr) +tensor([0.5578, 0.3211, 0.9645, ..., 0.0088, 0.4888, 0.8439]) +Matrix: as-caida_G_108 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105524 +Density: 0.0001071699546373339 +Time: 10.835067510604858 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_109.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_109.json new file mode 100644 index 0000000..cb9576b --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_109.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 157002, "MATRIX_FILE": "as-caida_G_109", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104802, "MATRIX_DENSITY": 0.00010643669294096003, "TIME_S": 10.484074115753174, "TIME_S_1KI": 0.06677669148006506, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1060.598595700264, "W": 103.78, "J_1KI": 6.7553190131352725, "W_1KI": 0.6610106877619394, "W_D": 68.89025000000001, "J_D": 704.0364464004637, "W_D_1KI": 0.4387858116457116, "J_D_1KI": 0.002794778484641671} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_109.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_109.output new file mode 100644 index 0000000..a52e2bf --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_109.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104801, 104801, + 104802]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104802, layout=torch.sparse_csr) +tensor([0.5767, 0.9923, 0.9583, ..., 0.7060, 0.7287, 0.7024]) +Matrix: as-caida_G_109 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104802 +Density: 0.00010643669294096003 +Time: 10.484074115753174 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_110.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_110.json new file mode 100644 index 0000000..6c8595f --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_110.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 157217, "MATRIX_FILE": "as-caida_G_110", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104846, "MATRIX_DENSITY": 0.0001064813792493263, "TIME_S": 10.386624813079834, "TIME_S_1KI": 0.0660655324365675, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1107.2109168171883, "W": 105.35, "J_1KI": 7.0425648423337694, "W_1KI": 0.6700929288817367, "W_D": 70.08324999999999, "J_D": 736.5632604274153, "W_D_1KI": 0.44577399390651135, "J_D_1KI": 0.0028354058015768735} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_110.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_110.output new file mode 100644 index 0000000..7ddf8ff --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_110.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104844, 104844, + 104846]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104846, layout=torch.sparse_csr) +tensor([0.6333, 0.9185, 0.9985, ..., 0.4370, 0.8961, 0.6971]) +Matrix: as-caida_G_110 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104846 +Density: 0.0001064813792493263 +Time: 10.386624813079834 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_111.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_111.json new file mode 100644 index 0000000..2c9ae52 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_111.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 153729, "MATRIX_FILE": "as-caida_G_111", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104766, "MATRIX_DENSITY": 0.00010640013141593308, "TIME_S": 10.289045572280884, "TIME_S_1KI": 0.06692976323452883, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1028.4533152198792, "W": 105.36, "J_1KI": 6.690041015162261, "W_1KI": 0.6853619030892024, "W_D": 69.76175, "J_D": 680.967189284742, "W_D_1KI": 0.45379694137085397, "J_D_1KI": 0.0029519280120917585} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_111.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_111.output new file mode 100644 index 0000000..cae7a5e --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_111.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104764, 104764, + 104766]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104766, layout=torch.sparse_csr) +tensor([0.9528, 0.0762, 0.5907, ..., 0.7328, 0.4022, 0.3839]) +Matrix: as-caida_G_111 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104766 +Density: 0.00010640013141593308 +Time: 10.289045572280884 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_112.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_112.json new file mode 100644 index 0000000..73d5354 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_112.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 155218, "MATRIX_FILE": "as-caida_G_112", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104730, "MATRIX_DENSITY": 0.00010636356989090612, "TIME_S": 10.327465057373047, "TIME_S_1KI": 0.06653522824268479, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1084.8732656860352, "W": 105.68, "J_1KI": 6.9893521736269975, "W_1KI": 0.6808488706206755, "W_D": 69.85150000000002, "J_D": 717.0706369991304, "W_D_1KI": 0.45002190467600417, "J_D_1KI": 0.0028992894166656197} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_112.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_112.output new file mode 100644 index 0000000..4ee6642 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_112.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104728, 104728, + 104730]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104730, layout=torch.sparse_csr) +tensor([0.1677, 0.2470, 0.5881, ..., 0.0756, 0.5116, 0.1287]) +Matrix: as-caida_G_112 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104730 +Density: 0.00010636356989090612 +Time: 10.327465057373047 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_113.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_113.json new file mode 100644 index 0000000..4d53d8a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_113.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 155391, "MATRIX_FILE": "as-caida_G_113", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105382, "MATRIX_DENSITY": 0.00010702573973306091, "TIME_S": 10.324763298034668, "TIME_S_1KI": 0.06644376635734804, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1121.859000439644, "W": 104.87, "J_1KI": 7.21958800985671, "W_1KI": 0.6748782104497687, "W_D": 69.12575000000001, "J_D": 739.4807361460926, "W_D_1KI": 0.4448504096118823, "J_D_1KI": 0.0028627810465978233} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_113.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_113.output new file mode 100644 index 0000000..c3bcfa7 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_113.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105381, 105381, + 105382]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105382, layout=torch.sparse_csr) +tensor([0.9685, 0.5826, 0.3326, ..., 0.9730, 0.1681, 0.2238]) +Matrix: as-caida_G_113 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105382 +Density: 0.00010702573973306091 +Time: 10.324763298034668 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_114.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_114.json new file mode 100644 index 0000000..bfaf19e --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_114.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 182298, "MATRIX_FILE": "as-caida_G_114", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 36406, "MATRIX_DENSITY": 3.6973857781422023e-05, "TIME_S": 10.05865478515625, "TIME_S_1KI": 0.05517698924374513, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1033.118657886982, "W": 100.25, "J_1KI": 5.667196885796783, "W_1KI": 0.5499237512205291, "W_D": 63.927, "J_D": 658.7947774837018, "W_D_1KI": 0.3506730737583517, "J_D_1KI": 0.0019236254580870427} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_114.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_114.output new file mode 100644 index 0000000..833068e --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_114.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 36405, 36405, 36406]), + col_indices=tensor([ 106, 329, 1040, ..., 1683, 1683, 12170]), + values=tensor([1., 1., 1., ..., 2., 2., 1.]), size=(31379, 31379), + nnz=36406, layout=torch.sparse_csr) +tensor([0.1561, 0.5541, 0.2105, ..., 0.0249, 0.8528, 0.2951]) +Matrix: as-caida_G_114 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 36406 +Density: 3.6973857781422023e-05 +Time: 10.05865478515625 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_115.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_115.json new file mode 100644 index 0000000..494070f --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_115.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 164014, "MATRIX_FILE": "as-caida_G_115", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106312, "MATRIX_DENSITY": 0.00010797024579625715, "TIME_S": 10.650753259658813, "TIME_S_1KI": 0.06493807394282691, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1138.4697159361838, "W": 105.76999999999998, "J_1KI": 6.9412959621506936, "W_1KI": 0.6448839733193507, "W_D": 70.49274999999997, "J_D": 758.7582591288683, "W_D_1KI": 0.4297971514626798, "J_D_1KI": 0.0026204906377667748} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_115.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_115.output new file mode 100644 index 0000000..aa96f8d --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_115.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106311, 106311, + 106312]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106312, layout=torch.sparse_csr) +tensor([0.4048, 0.9167, 0.0912, ..., 0.6295, 0.2862, 0.9856]) +Matrix: as-caida_G_115 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106312 +Density: 0.00010797024579625715 +Time: 10.650753259658813 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_116.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_116.json new file mode 100644 index 0000000..0da53ac --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_116.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 125120, "MATRIX_FILE": "as-caida_G_116", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106578, "MATRIX_DENSITY": 0.00010824039484228964, "TIME_S": 35.37350273132324, "TIME_S_1KI": 0.28271661390124075, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 880.3778803682327, "W": 104.13, "J_1KI": 7.03626822544943, "W_1KI": 0.8322410485933504, "W_D": 68.063, "J_D": 575.4456897292138, "W_D_1KI": 0.5439817774936062, "J_D_1KI": 0.004347680446719998} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_116.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_116.output new file mode 100644 index 0000000..c0b6846 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_116.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106577, 106577, + 106578]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106578, layout=torch.sparse_csr) +tensor([0.2001, 0.6845, 0.5928, ..., 0.6611, 0.5825, 0.1899]) +Matrix: as-caida_G_116 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106578 +Density: 0.00010824039484228964 +Time: 35.37350273132324 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_117.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_117.json new file mode 100644 index 0000000..37c276a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_117.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 156558, "MATRIX_FILE": "as-caida_G_117", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106348, "MATRIX_DENSITY": 0.0001080068073212841, "TIME_S": 10.432488441467285, "TIME_S_1KI": 0.06663657201463537, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1071.658259625435, "W": 105.39000000000001, "J_1KI": 6.845119761528858, "W_1KI": 0.6731690491702756, "W_D": 69.63750000000002, "J_D": 708.108948236704, "W_D_1KI": 0.4448032039244243, "J_D_1KI": 0.002841140049850051} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_117.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_117.output new file mode 100644 index 0000000..19957f0 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_117.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106347, 106347, + 106348]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106348, layout=torch.sparse_csr) +tensor([0.7751, 0.8016, 0.6971, ..., 0.1544, 0.3449, 0.2948]) +Matrix: as-caida_G_117 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106348 +Density: 0.0001080068073212841 +Time: 10.432488441467285 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_118.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_118.json new file mode 100644 index 0000000..436e523 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_118.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 160197, "MATRIX_FILE": "as-caida_G_118", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 107202, "MATRIX_DENSITY": 0.00010887412794275679, "TIME_S": 10.609473466873169, "TIME_S_1KI": 0.06622766635375923, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1084.652964963913, "W": 105.93, "J_1KI": 6.770744551795059, "W_1KI": 0.6612483379838574, "W_D": 70.65125, "J_D": 723.421955922842, "W_D_1KI": 0.44102729763978105, "J_D_1KI": 0.002753030940902645} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_118.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_118.output new file mode 100644 index 0000000..5d83786 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_118.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 107201, 107201, + 107202]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=107202, layout=torch.sparse_csr) +tensor([0.4290, 0.7908, 0.4960, ..., 0.6635, 0.5389, 0.1165]) +Matrix: as-caida_G_118 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 107202 +Density: 0.00010887412794275679 +Time: 10.609473466873169 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_119.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_119.json new file mode 100644 index 0000000..e43196a --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_119.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 156353, "MATRIX_FILE": "as-caida_G_119", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106462, "MATRIX_DENSITY": 0.00010812258548386945, "TIME_S": 10.173535823822021, "TIME_S_1KI": 0.06506773662048072, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1132.5900715255739, "W": 105.04000000000002, "J_1KI": 7.243801343917762, "W_1KI": 0.6718131407775995, "W_D": 68.36050000000002, "J_D": 737.0946647422315, "W_D_1KI": 0.4372189852449267, "J_D_1KI": 0.0027963581462775045} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_119.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_119.output new file mode 100644 index 0000000..d4a05e9 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_119.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106461, 106461, + 106462]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106462, layout=torch.sparse_csr) +tensor([0.1121, 0.0026, 0.9086, ..., 0.5451, 0.2166, 0.4573]) +Matrix: as-caida_G_119 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106462 +Density: 0.00010812258548386945 +Time: 10.173535823822021 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_120.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_120.json new file mode 100644 index 0000000..08346d6 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_120.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 153165, "MATRIX_FILE": "as-caida_G_120", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106510, "MATRIX_DENSITY": 0.0001081713341839054, "TIME_S": 10.037507057189941, "TIME_S_1KI": 0.06553394742395417, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1056.7669794702529, "W": 104.90999999999998, "J_1KI": 6.899533049131674, "W_1KI": 0.6849476055234549, "W_D": 69.5015, "J_D": 700.0942734119891, "W_D_1KI": 0.4537688114125289, "J_D_1KI": 0.0029626142487678576} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_120.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_120.output new file mode 100644 index 0000000..9766930 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_120.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106509, 106509, + 106510]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106510, layout=torch.sparse_csr) +tensor([0.6727, 0.9196, 0.4389, ..., 0.2721, 0.4222, 0.7940]) +Matrix: as-caida_G_120 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106510 +Density: 0.0001081713341839054 +Time: 10.037507057189941 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_121.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_121.json new file mode 100644 index 0000000..bd5c0c7 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_121.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 157692, "MATRIX_FILE": "as-caida_G_121", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106762, "MATRIX_DENSITY": 0.00010842726485909405, "TIME_S": 10.233589172363281, "TIME_S_1KI": 0.06489605796339244, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1092.8619159030914, "W": 105.66999999999999, "J_1KI": 6.930357379594978, "W_1KI": 0.6701037465438956, "W_D": 70.15825, "J_D": 725.5917432706356, "W_D_1KI": 0.44490684372067063, "J_D_1KI": 0.0028213659774793307} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_121.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_121.output new file mode 100644 index 0000000..7125027 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_121.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106761, 106761, + 106762]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106762, layout=torch.sparse_csr) +tensor([0.1317, 0.2698, 0.0530, ..., 0.9345, 0.4572, 0.0045]) +Matrix: as-caida_G_121 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106762 +Density: 0.00010842726485909405 +Time: 10.233589172363281 seconds + diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_122.json b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_122.json new file mode 100644 index 0000000..70578b0 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_122.json @@ -0,0 +1 @@ +{"CPU": "EPYC_7313P", "ITERATIONS": 164498, "MATRIX_FILE": "as-caida_G_122", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105722, "MATRIX_DENSITY": 0.00010737104302498212, "TIME_S": 10.548460245132446, "TIME_S_1KI": 0.06412515802704255, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 1153.0029864287376, "W": 105.83, "J_1KI": 7.009221914118942, "W_1KI": 0.643351286945738, "W_D": 70.53049999999999, "J_D": 768.4198916593789, "W_D_1KI": 0.4287620518182591, "J_D_1KI": 0.0026064879318791665} diff --git a/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_122.output b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_122.output new file mode 100644 index 0000000..471b753 --- /dev/null +++ b/pytorch/output_as-caida/epyc_7313p_10_10_10_as-caida_G_122.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105721, 105721, + 105722]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105722, layout=torch.sparse_csr) +tensor([0.4694, 0.4038, 0.5199, ..., 0.0710, 0.9245, 0.8120]) +Matrix: as-caida_G_122 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105722 +Density: 0.00010737104302498212 +Time: 10.548460245132446 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida.json new file mode 100644 index 0000000..293be90 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 94777, "MATRIX_FILE": "as-caida", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106762, "MATRIX_DENSITY": 0.00010842726485909405, "TIME_S": 10.596776962280273, "TIME_S_1KI": 0.11180747398926189, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 749.1460662841796, "W": 72.32, "J_1KI": 7.904302375936985, "W_1KI": 0.7630543275267205, "W_D": 55.543749999999996, "J_D": 575.3647928535938, "W_D_1KI": 0.5860467201958282, "J_D_1KI": 0.00618342762691189} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida.output new file mode 100644 index 0000000..a40453f --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106761, 106761, + 106762]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106762, layout=torch.sparse_csr) +tensor([0.2456, 0.4653, 0.4196, ..., 0.3745, 0.8264, 0.7070]) +Matrix: as-caida +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106762 +Density: 0.00010842726485909405 +Time: 10.596776962280273 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_001.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_001.json new file mode 100644 index 0000000..97d103a --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_001.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 104686, "MATRIX_FILE": "as-caida_G_001", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 65910, "MATRIX_DENSITY": 6.693805873684353e-05, "TIME_S": 10.144171953201294, "TIME_S_1KI": 0.09690094141720282, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 742.1725367832184, "W": 72.98, "J_1KI": 7.089510887637491, "W_1KI": 0.6971323768221157, "W_D": 56.504000000000005, "J_D": 574.6193069114686, "W_D_1KI": 0.5397474351871311, "J_D_1KI": 0.0051558702709734935} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_001.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_001.output new file mode 100644 index 0000000..e367857 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_001.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 148, 148, ..., 65909, 65909, 65910]), + col_indices=tensor([ 51, 111, 117, ..., 978, 8230, 12170]), + values=tensor([3., 4., 3., ..., 2., 1., 1.]), size=(31379, 31379), + nnz=65910, layout=torch.sparse_csr) +tensor([0.8662, 0.9285, 0.9220, ..., 0.3436, 0.8270, 0.3172]) +Matrix: as-caida_G_001 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 65910 +Density: 6.693805873684353e-05 +Time: 10.144171953201294 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_002.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_002.json new file mode 100644 index 0000000..e4a5fb3 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_002.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 105438, "MATRIX_FILE": "as-caida_G_002", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 66744, "MATRIX_DENSITY": 6.77850673999679e-05, "TIME_S": 10.661542177200317, "TIME_S_1KI": 0.10111669585159352, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 773.6142930841446, "W": 73.06, "J_1KI": 7.337148780175502, "W_1KI": 0.6929190614389499, "W_D": 56.844500000000004, "J_D": 601.9123690558672, "W_D_1KI": 0.5391272596217682, "J_D_1KI": 0.005113215914772361} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_002.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_002.output new file mode 100644 index 0000000..128af31 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_002.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 129, 129, ..., 66743, 66743, 66744]), + col_indices=tensor([ 51, 111, 117, ..., 978, 8230, 12170]), + values=tensor([3., 4., 3., ..., 2., 1., 1.]), size=(31379, 31379), + nnz=66744, layout=torch.sparse_csr) +tensor([0.6975, 0.5868, 0.1612, ..., 0.8167, 0.6393, 0.3667]) +Matrix: as-caida_G_002 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 66744 +Density: 6.77850673999679e-05 +Time: 10.661542177200317 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_003.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_003.json new file mode 100644 index 0000000..c996750 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_003.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 105093, "MATRIX_FILE": "as-caida_G_003", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 66680, "MATRIX_DENSITY": 6.772006913325332e-05, "TIME_S": 10.217018127441406, "TIME_S_1KI": 0.09721882644363951, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 751.2508925914764, "W": 73.38, "J_1KI": 7.148438931151231, "W_1KI": 0.6982387028631782, "W_D": 56.80924999999999, "J_D": 581.6026133817434, "W_D_1KI": 0.5405616929766967, "J_D_1KI": 0.0051436507947883936} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_003.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_003.output new file mode 100644 index 0000000..9c883cd --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_003.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 89, 89, ..., 66679, 66679, 66680]), + col_indices=tensor([ 51, 111, 117, ..., 978, 978, 12170]), + values=tensor([3., 4., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=66680, layout=torch.sparse_csr) +tensor([0.6508, 0.4047, 0.6325, ..., 0.4294, 0.9351, 0.5887]) +Matrix: as-caida_G_003 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 66680 +Density: 6.772006913325332e-05 +Time: 10.217018127441406 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_004.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_004.json new file mode 100644 index 0000000..5cf7af5 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_004.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 103252, "MATRIX_FILE": "as-caida_G_004", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 68670, "MATRIX_DENSITY": 6.97411089889098e-05, "TIME_S": 10.702553987503052, "TIME_S_1KI": 0.10365468937650653, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 767.785103738308, "W": 72.95, "J_1KI": 7.436031299522605, "W_1KI": 0.7065238445744393, "W_D": 56.59075, "J_D": 595.6070577022433, "W_D_1KI": 0.548083814357107, "J_D_1KI": 0.0053082149920302465} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_004.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_004.output new file mode 100644 index 0000000..f05fd58 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_004.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 62, 62, ..., 68669, 68669, 68670]), + col_indices=tensor([ 111, 822, 875, ..., 160, 4019, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=68670, layout=torch.sparse_csr) +tensor([0.0158, 0.7542, 0.7171, ..., 0.0987, 0.8416, 0.8627]) +Matrix: as-caida_G_004 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 68670 +Density: 6.97411089889098e-05 +Time: 10.702553987503052 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_005.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_005.json new file mode 100644 index 0000000..ac55c52 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_005.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 103836, "MATRIX_FILE": "as-caida_G_005", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 70026, "MATRIX_DENSITY": 7.111825976492498e-05, "TIME_S": 10.64279055595398, "TIME_S_1KI": 0.10249615312564024, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 786.0960059285164, "W": 73.45, "J_1KI": 7.57055362233249, "W_1KI": 0.7073654609191418, "W_D": 56.849500000000006, "J_D": 608.429746617198, "W_D_1KI": 0.5474931622943874, "J_D_1KI": 0.005272671927793707} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_005.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_005.output new file mode 100644 index 0000000..a4deaa3 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_005.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 63, 63, ..., 70025, 70025, 70026]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=70026, layout=torch.sparse_csr) +tensor([0.4421, 0.6524, 0.9248, ..., 0.0106, 0.6325, 0.5599]) +Matrix: as-caida_G_005 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 70026 +Density: 7.111825976492498e-05 +Time: 10.64279055595398 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_006.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_006.json new file mode 100644 index 0000000..c720f07 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_006.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 102487, "MATRIX_FILE": "as-caida_G_006", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 71094, "MATRIX_DENSITY": 7.220291834072453e-05, "TIME_S": 10.558621406555176, "TIME_S_1KI": 0.10302400701118362, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 770.917197034359, "W": 73.19, "J_1KI": 7.522097407811322, "W_1KI": 0.7141393542595647, "W_D": 56.419, "J_D": 594.2666667506694, "W_D_1KI": 0.5504990876891703, "J_D_1KI": 0.00537140405796999} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_006.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_006.output new file mode 100644 index 0000000..1d54156 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_006.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 60, 60, ..., 71093, 71093, 71094]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=71094, layout=torch.sparse_csr) +tensor([0.8094, 0.3556, 0.1158, ..., 0.4122, 0.8299, 0.0229]) +Matrix: as-caida_G_006 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 71094 +Density: 7.220291834072453e-05 +Time: 10.558621406555176 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_007.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_007.json new file mode 100644 index 0000000..3c860d0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_007.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 100972, "MATRIX_FILE": "as-caida_G_007", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 71658, "MATRIX_DENSITY": 7.277571556614678e-05, "TIME_S": 10.574648380279541, "TIME_S_1KI": 0.10472852256347841, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 767.2342040729524, "W": 72.76, "J_1KI": 7.598484768777011, "W_1KI": 0.7205958087390564, "W_D": 56.43150000000001, "J_D": 595.0546589766742, "W_D_1KI": 0.5588826605395556, "J_D_1KI": 0.005535026151205835} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_007.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_007.output new file mode 100644 index 0000000..14e3e3f --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_007.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 57, 57, ..., 71657, 71657, 71658]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=71658, layout=torch.sparse_csr) +tensor([0.5212, 0.6472, 0.5886, ..., 0.5043, 0.1273, 0.2185]) +Matrix: as-caida_G_007 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 71658 +Density: 7.277571556614678e-05 +Time: 10.574648380279541 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_008.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_008.json new file mode 100644 index 0000000..ccfe704 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_008.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99488, "MATRIX_FILE": "as-caida_G_008", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 72140, "MATRIX_DENSITY": 7.326523376234096e-05, "TIME_S": 10.236967325210571, "TIME_S_1KI": 0.10289650334925389, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 765.4581503081322, "W": 72.89, "J_1KI": 7.69397465330625, "W_1KI": 0.732651174010936, "W_D": 56.16425, "J_D": 589.811811201036, "W_D_1KI": 0.5645329084914763, "J_D_1KI": 0.005674381920346939} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_008.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_008.output new file mode 100644 index 0000000..f346135 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_008.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 55, 55, ..., 72139, 72139, 72140]), + col_indices=tensor([ 111, 761, 822, ..., 978, 978, 12170]), + values=tensor([4., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=72140, layout=torch.sparse_csr) +tensor([0.6519, 0.0842, 0.0714, ..., 0.1636, 0.2367, 0.3237]) +Matrix: as-caida_G_008 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 72140 +Density: 7.326523376234096e-05 +Time: 10.236967325210571 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_009.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_009.json new file mode 100644 index 0000000..f2ce137 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_009.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 103075, "MATRIX_FILE": "as-caida_G_009", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 74344, "MATRIX_DENSITY": 7.550361157232432e-05, "TIME_S": 10.777665615081787, "TIME_S_1KI": 0.10456139330663873, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 780.9051319265366, "W": 73.69, "J_1KI": 7.576086654635329, "W_1KI": 0.7149163230657288, "W_D": 47.38175, "J_D": 502.1122504364252, "W_D_1KI": 0.459682270191608, "J_D_1KI": 0.004459687316920766} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_009.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_009.output new file mode 100644 index 0000000..3cf9d75 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_009.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 38, 38, ..., 74343, 74343, 74344]), + col_indices=tensor([ 111, 875, 1040, ..., 160, 4019, 12170]), + values=tensor([4., 3., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=74344, layout=torch.sparse_csr) +tensor([0.5560, 0.3103, 0.6263, ..., 0.1568, 0.2984, 0.1260]) +Matrix: as-caida_G_009 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 74344 +Density: 7.550361157232432e-05 +Time: 10.777665615081787 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_010.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_010.json new file mode 100644 index 0000000..3afa769 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_010.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99873, "MATRIX_FILE": "as-caida_G_010", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 74994, "MATRIX_DENSITY": 7.616375021864427e-05, "TIME_S": 10.477545976638794, "TIME_S_1KI": 0.10490869380752349, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 766.0216178941727, "W": 73.02, "J_1KI": 7.669957024362667, "W_1KI": 0.7311285332372112, "W_D": 56.2405, "J_D": 589.9950534261465, "W_D_1KI": 0.5631201626065102, "J_D_1KI": 0.005638362346244833} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_010.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_010.output new file mode 100644 index 0000000..0d64584 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_010.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 28, 28, ..., 74993, 74993, 74994]), + col_indices=tensor([ 1040, 2020, 2054, ..., 160, 160, 12170]), + values=tensor([1., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=74994, layout=torch.sparse_csr) +tensor([0.6988, 0.6266, 0.9846, ..., 0.6539, 0.4334, 0.1114]) +Matrix: as-caida_G_010 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 74994 +Density: 7.616375021864427e-05 +Time: 10.477545976638794 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_011.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_011.json new file mode 100644 index 0000000..36ffeba --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_011.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 101004, "MATRIX_FILE": "as-caida_G_011", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 75118, "MATRIX_DENSITY": 7.628968436040377e-05, "TIME_S": 10.700015544891357, "TIME_S_1KI": 0.10593655246219315, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 762.429067940712, "W": 73.17, "J_1KI": 7.548503702236664, "W_1KI": 0.7244267553760247, "W_D": 56.37775, "J_D": 587.4543581398725, "W_D_1KI": 0.558173438675696, "J_D_1KI": 0.005526250828439429} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_011.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_011.output new file mode 100644 index 0000000..d9ac653 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_011.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 25, 25, ..., 75117, 75117, 75118]), + col_indices=tensor([ 1040, 2020, 2054, ..., 160, 160, 12170]), + values=tensor([1., 3., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=75118, layout=torch.sparse_csr) +tensor([0.7297, 0.3714, 0.1530, ..., 0.2477, 0.9969, 0.7150]) +Matrix: as-caida_G_011 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 75118 +Density: 7.628968436040377e-05 +Time: 10.700015544891357 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_012.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_012.json new file mode 100644 index 0000000..3da7084 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_012.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98762, "MATRIX_FILE": "as-caida_G_012", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 76530, "MATRIX_DENSITY": 7.772370861979419e-05, "TIME_S": 10.461997032165527, "TIME_S_1KI": 0.10593140106686304, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 775.8345263957978, "W": 73.56, "J_1KI": 7.855597561772725, "W_1KI": 0.7448208825256678, "W_D": 57.0745, "J_D": 601.9625839692354, "W_D_1KI": 0.577899394503959, "J_D_1KI": 0.005851434706708643} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_012.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_012.output new file mode 100644 index 0000000..9a6f448 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_012.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 76530, 76530, 76530]), + col_indices=tensor([1040, 2054, 5699, ..., 160, 160, 7454]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=76530, layout=torch.sparse_csr) +tensor([0.8981, 0.1737, 0.5583, ..., 0.5102, 0.9613, 0.9792]) +Matrix: as-caida_G_012 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 76530 +Density: 7.772370861979419e-05 +Time: 10.461997032165527 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_013.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_013.json new file mode 100644 index 0000000..4f413c0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_013.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99602, "MATRIX_FILE": "as-caida_G_013", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 77002, "MATRIX_DENSITY": 7.820307083681422e-05, "TIME_S": 10.601778030395508, "TIME_S_1KI": 0.10644141714418895, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 767.6239194512367, "W": 72.85, "J_1KI": 7.7069127070865715, "W_1KI": 0.7314110158430553, "W_D": 56.51125, "J_D": 595.4617325749992, "W_D_1KI": 0.5673706351278086, "J_D_1KI": 0.005696377935461221} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_013.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_013.output new file mode 100644 index 0000000..3c833de --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_013.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 5, 5, ..., 77002, 77002, 77002]), + col_indices=tensor([1040, 2054, 2150, ..., 160, 8230, 7454]), + values=tensor([1., 1., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=77002, layout=torch.sparse_csr) +tensor([0.2269, 0.9429, 0.7851, ..., 0.1874, 0.2871, 0.9322]) +Matrix: as-caida_G_013 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 77002 +Density: 7.820307083681422e-05 +Time: 10.601778030395508 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_014.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_014.json new file mode 100644 index 0000000..a9a2d31 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_014.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99661, "MATRIX_FILE": "as-caida_G_014", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 75982, "MATRIX_DENSITY": 7.71671609610506e-05, "TIME_S": 10.43959665298462, "TIME_S_1KI": 0.10475107266618455, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 769.1122263169287, "W": 73.07, "J_1KI": 7.717283855439226, "W_1KI": 0.7331854988410711, "W_D": 56.397749999999995, "J_D": 593.6252779768109, "W_D_1KI": 0.5658958870571236, "J_D_1KI": 0.005678207995676579} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_014.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_014.output new file mode 100644 index 0000000..4767f85 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_014.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 5, 5, ..., 75982, 75982, 75982]), + col_indices=tensor([1040, 2054, 2150, ..., 160, 160, 8230]), + values=tensor([1., 1., 3., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=75982, layout=torch.sparse_csr) +tensor([0.7101, 0.6212, 0.4402, ..., 0.3877, 0.6312, 0.4139]) +Matrix: as-caida_G_014 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 75982 +Density: 7.71671609610506e-05 +Time: 10.43959665298462 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_015.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_015.json new file mode 100644 index 0000000..25fdd1e --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_015.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 100487, "MATRIX_FILE": "as-caida_G_015", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 77124, "MATRIX_DENSITY": 7.832697378273889e-05, "TIME_S": 10.586341619491577, "TIME_S_1KI": 0.10535035994199825, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 771.3371865081787, "W": 72.74, "J_1KI": 7.675989794781202, "W_1KI": 0.7238747300645854, "W_D": 55.977999999999994, "J_D": 593.5924254379272, "W_D_1KI": 0.557067083304308, "J_D_1KI": 0.0055436731448277685} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_015.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_015.output new file mode 100644 index 0000000..db10b2c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_015.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 4, 4, ..., 77124, 77124, 77124]), + col_indices=tensor([1040, 2054, 4842, ..., 160, 160, 8230]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=77124, layout=torch.sparse_csr) +tensor([0.7250, 0.8849, 0.5072, ..., 0.9949, 0.7755, 0.5247]) +Matrix: as-caida_G_015 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 77124 +Density: 7.832697378273889e-05 +Time: 10.586341619491577 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_016.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_016.json new file mode 100644 index 0000000..1ef9533 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_016.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 100200, "MATRIX_FILE": "as-caida_G_016", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 77860, "MATRIX_DENSITY": 7.907445384995657e-05, "TIME_S": 10.545039176940918, "TIME_S_1KI": 0.10523991194551814, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 771.6631873869896, "W": 72.89, "J_1KI": 7.701229415039817, "W_1KI": 0.7274451097804392, "W_D": 56.263000000000005, "J_D": 595.6384402792454, "W_D_1KI": 0.5615069860279442, "J_D_1KI": 0.005603862136007427} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_016.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_016.output new file mode 100644 index 0000000..a838b90 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_016.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 77856, 77858, 77860]), + col_indices=tensor([ 1040, 4842, 5699, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=77860, layout=torch.sparse_csr) +tensor([0.5000, 0.6003, 0.8574, ..., 0.0977, 0.2678, 0.2345]) +Matrix: as-caida_G_016 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 77860 +Density: 7.907445384995657e-05 +Time: 10.545039176940918 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_017.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_017.json new file mode 100644 index 0000000..130864e --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_017.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99177, "MATRIX_FILE": "as-caida_G_017", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 79718, "MATRIX_DENSITY": 8.096143478051423e-05, "TIME_S": 10.514747381210327, "TIME_S_1KI": 0.10602001856489233, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 783.8662980437279, "W": 73.05, "J_1KI": 7.9037105180004215, "W_1KI": 0.7365619044738194, "W_D": 56.455749999999995, "J_D": 605.8009549046159, "W_D_1KI": 0.5692423646611613, "J_D_1KI": 0.005739661057111641} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_017.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_017.output new file mode 100644 index 0000000..f0cd2b4 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_017.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 79714, 79716, 79718]), + col_indices=tensor([ 1040, 5699, 33, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 4., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=79718, layout=torch.sparse_csr) +tensor([0.4528, 0.4646, 0.6572, ..., 0.6265, 0.0742, 0.0179]) +Matrix: as-caida_G_017 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 79718 +Density: 8.096143478051423e-05 +Time: 10.514747381210327 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_018.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_018.json new file mode 100644 index 0000000..18bd5f9 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_018.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99395, "MATRIX_FILE": "as-caida_G_018", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 80396, "MATRIX_DENSITY": 8.16500101685218e-05, "TIME_S": 10.922678470611572, "TIME_S_1KI": 0.10989162906194046, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 766.4679673075675, "W": 72.99, "J_1KI": 7.711333239172669, "W_1KI": 0.7343427737813774, "W_D": 56.57874999999999, "J_D": 594.1334361597894, "W_D_1KI": 0.5692313496654761, "J_D_1KI": 0.005726961614422014} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_018.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_018.output new file mode 100644 index 0000000..40fa031 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_018.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 80392, 80394, 80396]), + col_indices=tensor([ 1040, 5282, 5699, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=80396, layout=torch.sparse_csr) +tensor([0.1730, 0.0579, 0.0708, ..., 0.7902, 0.1397, 0.8226]) +Matrix: as-caida_G_018 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 80396 +Density: 8.16500101685218e-05 +Time: 10.922678470611572 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_019.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_019.json new file mode 100644 index 0000000..30a1448 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_019.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96832, "MATRIX_FILE": "as-caida_G_019", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 80970, "MATRIX_DENSITY": 8.22329633731182e-05, "TIME_S": 10.339067697525024, "TIME_S_1KI": 0.10677325365091112, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 763.8780684614181, "W": 72.94, "J_1KI": 7.888694527237051, "W_1KI": 0.7532633840052876, "W_D": 56.62525, "J_D": 593.0187358945012, "W_D_1KI": 0.5847782757766028, "J_D_1KI": 0.0060391014930663706} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_019.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_019.output new file mode 100644 index 0000000..1f29c09 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_019.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 80966, 80968, 80970]), + col_indices=tensor([ 1040, 5699, 106, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=80970, layout=torch.sparse_csr) +tensor([0.6840, 0.0068, 0.0075, ..., 0.7573, 0.5640, 0.2811]) +Matrix: as-caida_G_019 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 80970 +Density: 8.22329633731182e-05 +Time: 10.339067697525024 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_020.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_020.json new file mode 100644 index 0000000..9cc08f5 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_020.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99669, "MATRIX_FILE": "as-caida_G_020", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 80948, "MATRIX_DENSITY": 8.221062021893506e-05, "TIME_S": 10.569360256195068, "TIME_S_1KI": 0.1060446102217848, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 772.5310431408882, "W": 72.71, "J_1KI": 7.750966129296854, "W_1KI": 0.7295146936359348, "W_D": 56.27325, "J_D": 597.8934468907713, "W_D_1KI": 0.564601330403636, "J_D_1KI": 0.0056647636717899845} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_020.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_020.output new file mode 100644 index 0000000..69fa6d4 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_020.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 80944, 80946, 80948]), + col_indices=tensor([ 1040, 5699, 106, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=80948, layout=torch.sparse_csr) +tensor([0.7094, 0.8366, 0.9995, ..., 0.9571, 0.8455, 0.5454]) +Matrix: as-caida_G_020 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 80948 +Density: 8.221062021893506e-05 +Time: 10.569360256195068 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_021.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_021.json new file mode 100644 index 0000000..c3e6887 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_021.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97260, "MATRIX_FILE": "as-caida_G_021", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 81882, "MATRIX_DENSITY": 8.315918867380097e-05, "TIME_S": 10.350789546966553, "TIME_S_1KI": 0.10642391062067193, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 756.8842212677001, "W": 72.85, "J_1KI": 7.78207095689595, "W_1KI": 0.7490232366851737, "W_D": 56.485749999999996, "J_D": 586.8657913722991, "W_D_1KI": 0.5807706148468024, "J_D_1KI": 0.005971320325383532} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_021.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_021.output new file mode 100644 index 0000000..df99054 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_021.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 81878, 81880, 81882]), + col_indices=tensor([ 1040, 5699, 106, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=81882, layout=torch.sparse_csr) +tensor([0.6338, 0.5148, 0.0178, ..., 0.3856, 0.4274, 0.9796]) +Matrix: as-caida_G_021 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 81882 +Density: 8.315918867380097e-05 +Time: 10.350789546966553 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_022.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_022.json new file mode 100644 index 0000000..73900be --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_022.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97348, "MATRIX_FILE": "as-caida_G_022", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 82138, "MATRIX_DENSITY": 8.341918174065929e-05, "TIME_S": 10.487600326538086, "TIME_S_1KI": 0.10773308467085185, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 755.768605053425, "W": 72.65, "J_1KI": 7.76357608839858, "W_1KI": 0.7462916546821713, "W_D": 55.925250000000005, "J_D": 581.7831821027398, "W_D_1KI": 0.5744879196285492, "J_D_1KI": 0.005901383897240304} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_022.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_022.output new file mode 100644 index 0000000..8e23967 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_022.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 82134, 82136, 82138]), + col_indices=tensor([ 106, 329, 1040, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=82138, layout=torch.sparse_csr) +tensor([0.1794, 0.9721, 0.7785, ..., 0.3109, 0.4955, 0.6848]) +Matrix: as-caida_G_022 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 82138 +Density: 8.341918174065929e-05 +Time: 10.487600326538086 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_023.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_023.json new file mode 100644 index 0000000..7e9b9f2 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_023.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97571, "MATRIX_FILE": "as-caida_G_023", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 83524, "MATRIX_DENSITY": 8.482680045419692e-05, "TIME_S": 10.370388269424438, "TIME_S_1KI": 0.10628555892042142, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 748.4717112731934, "W": 72.64, "J_1KI": 7.671046840487372, "W_1KI": 0.744483504319931, "W_D": 56.2095, "J_D": 579.1742931554318, "W_D_1KI": 0.5760881819393058, "J_D_1KI": 0.005904297198340755} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_023.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_023.output new file mode 100644 index 0000000..0f6e5b0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_023.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 83520, 83522, 83524]), + col_indices=tensor([ 106, 329, 1040, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=83524, layout=torch.sparse_csr) +tensor([0.4422, 0.7878, 0.4866, ..., 0.4700, 0.4641, 0.8768]) +Matrix: as-caida_G_023 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 83524 +Density: 8.482680045419692e-05 +Time: 10.370388269424438 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_024.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_024.json new file mode 100644 index 0000000..4a7c57b --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_024.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99634, "MATRIX_FILE": "as-caida_G_024", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 83640, "MATRIX_DENSITY": 8.49446098126171e-05, "TIME_S": 10.725587368011475, "TIME_S_1KI": 0.10764987221241216, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 772.4394788742065, "W": 73.0, "J_1KI": 7.752769926673691, "W_1KI": 0.7326816147098381, "W_D": 56.62675, "J_D": 599.1881816484928, "W_D_1KI": 0.5683476524078126, "J_D_1KI": 0.005704354461406875} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_024.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_024.output new file mode 100644 index 0000000..2affe55 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_024.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 83636, 83638, 83640]), + col_indices=tensor([ 106, 329, 1040, ..., 31378, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=83640, layout=torch.sparse_csr) +tensor([0.3695, 0.3941, 0.0385, ..., 0.1991, 0.5028, 0.5775]) +Matrix: as-caida_G_024 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 83640 +Density: 8.49446098126171e-05 +Time: 10.725587368011475 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_025.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_025.json new file mode 100644 index 0000000..162bcd0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_025.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96268, "MATRIX_FILE": "as-caida_G_025", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85850, "MATRIX_DENSITY": 8.718908121010495e-05, "TIME_S": 10.428590059280396, "TIME_S_1KI": 0.10832872874974442, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 756.1684657931329, "W": 72.79, "J_1KI": 7.854826793878889, "W_1KI": 0.7561183363111315, "W_D": 56.42125000000001, "J_D": 586.124056197703, "W_D_1KI": 0.5860851996509744, "J_D_1KI": 0.006088058333516583} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_025.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_025.output new file mode 100644 index 0000000..1c5fb59 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_025.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 3, 3, ..., 85845, 85847, 85850]), + col_indices=tensor([ 346, 13811, 21783, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=85850, layout=torch.sparse_csr) +tensor([0.1097, 0.8069, 0.8061, ..., 0.5729, 0.7458, 0.7275]) +Matrix: as-caida_G_025 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85850 +Density: 8.718908121010495e-05 +Time: 10.428590059280396 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_026.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_026.json new file mode 100644 index 0000000..aea4b72 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_026.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99303, "MATRIX_FILE": "as-caida_G_026", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85468, "MATRIX_DENSITY": 8.68011228056523e-05, "TIME_S": 10.634388446807861, "TIME_S_1KI": 0.10709030388616518, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 771.4423669743538, "W": 72.73, "J_1KI": 7.768570606873446, "W_1KI": 0.7324048618873549, "W_D": 56.414750000000005, "J_D": 598.3875742096305, "W_D_1KI": 0.568107207234424, "J_D_1KI": 0.00572094707344616} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_026.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_026.output new file mode 100644 index 0000000..a144a69 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_026.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 85463, 85465, 85468]), + col_indices=tensor([21783, 106, 329, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=85468, layout=torch.sparse_csr) +tensor([0.8255, 0.6212, 0.4619, ..., 0.1684, 0.7840, 0.3609]) +Matrix: as-caida_G_026 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85468 +Density: 8.68011228056523e-05 +Time: 10.634388446807861 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_027.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_027.json new file mode 100644 index 0000000..20fe7fa --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_027.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98820, "MATRIX_FILE": "as-caida_G_027", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85744, "MATRIX_DENSITY": 8.708142783085892e-05, "TIME_S": 10.608806848526001, "TIME_S_1KI": 0.10735485578350537, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 764.8988233160973, "W": 72.77, "J_1KI": 7.740324057033973, "W_1KI": 0.7363893948593402, "W_D": 56.111999999999995, "J_D": 589.8035285682678, "W_D_1KI": 0.567820279295689, "J_D_1KI": 0.005746005659741844} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_027.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_027.output new file mode 100644 index 0000000..2c92d41 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_027.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 85739, 85741, 85744]), + col_indices=tensor([21783, 106, 329, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=85744, layout=torch.sparse_csr) +tensor([0.0463, 0.3441, 0.5339, ..., 0.0453, 0.3348, 0.9115]) +Matrix: as-caida_G_027 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85744 +Density: 8.708142783085892e-05 +Time: 10.608806848526001 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_028.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_028.json new file mode 100644 index 0000000..6151d14 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_028.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96352, "MATRIX_FILE": "as-caida_G_028", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 84962, "MATRIX_DENSITY": 8.628723025944015e-05, "TIME_S": 10.367092847824097, "TIME_S_1KI": 0.1075960317152119, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 764.7028366541862, "W": 72.69, "J_1KI": 7.936553851027339, "W_1KI": 0.7544212886084357, "W_D": 55.928749999999994, "J_D": 588.3735558608174, "W_D_1KI": 0.5804627822982398, "J_D_1KI": 0.006024397856798403} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_028.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_028.output new file mode 100644 index 0000000..fecbbcb --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_028.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 84957, 84959, 84962]), + col_indices=tensor([ 1809, 21783, 106, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=84962, layout=torch.sparse_csr) +tensor([0.1094, 0.2193, 0.6022, ..., 0.9471, 0.3516, 0.1626]) +Matrix: as-caida_G_028 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 84962 +Density: 8.628723025944015e-05 +Time: 10.367092847824097 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_029.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_029.json new file mode 100644 index 0000000..3ae3b54 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_029.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96326, "MATRIX_FILE": "as-caida_G_029", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 86566, "MATRIX_DENSITY": 8.791624931897431e-05, "TIME_S": 10.383660793304443, "TIME_S_1KI": 0.1077970723719914, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 755.9279503822327, "W": 73.0, "J_1KI": 7.847600340325901, "W_1KI": 0.7578431576106139, "W_D": 56.679, "J_D": 586.92109999609, "W_D_1KI": 0.588408114112493, "J_D_1KI": 0.006108507714557784} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_029.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_029.output new file mode 100644 index 0000000..3490f59 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_029.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 86561, 86563, 86566]), + col_indices=tensor([ 1809, 21783, 106, ..., 15310, 17998, 31377]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=86566, layout=torch.sparse_csr) +tensor([0.5008, 0.6590, 0.8656, ..., 0.8761, 0.6069, 0.5150]) +Matrix: as-caida_G_029 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 86566 +Density: 8.791624931897431e-05 +Time: 10.383660793304443 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_030.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_030.json new file mode 100644 index 0000000..034fac0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_030.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96189, "MATRIX_FILE": "as-caida_G_030", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 86850, "MATRIX_DENSITY": 8.820467912752026e-05, "TIME_S": 10.468584775924683, "TIME_S_1KI": 0.10883349214488852, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 754.0782526731491, "W": 73.05, "J_1KI": 7.839547689165592, "W_1KI": 0.759442347877616, "W_D": 56.626749999999994, "J_D": 584.5448418146372, "W_D_1KI": 0.588702970194097, "J_D_1KI": 0.006120273318093514} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_030.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_030.output new file mode 100644 index 0000000..14e1bf0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_030.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 86850, 86850, 86850]), + col_indices=tensor([ 1809, 21783, 106, ..., 7018, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=86850, layout=torch.sparse_csr) +tensor([0.2999, 0.1251, 0.7043, ..., 0.0831, 0.2185, 0.1274]) +Matrix: as-caida_G_030 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 86850 +Density: 8.820467912752026e-05 +Time: 10.468584775924683 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_031.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_031.json new file mode 100644 index 0000000..b0c6e73 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_031.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97502, "MATRIX_FILE": "as-caida_G_031", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87232, "MATRIX_DENSITY": 8.859263753197291e-05, "TIME_S": 10.472068786621094, "TIME_S_1KI": 0.10740363055753825, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 763.1660771083832, "W": 72.42, "J_1KI": 7.827183822981921, "W_1KI": 0.7427539947898505, "W_D": 55.92375, "J_D": 589.327656789422, "W_D_1KI": 0.573565157637792, "J_D_1KI": 0.0058825988968204965} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_031.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_031.output new file mode 100644 index 0000000..ee7c035 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_031.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87232, 87232, 87232]), + col_indices=tensor([ 1809, 21783, 106, ..., 1101, 16290, 882]), + values=tensor([1., 1., 1., ..., 2., 1., 1.]), size=(31379, 31379), + nnz=87232, layout=torch.sparse_csr) +tensor([0.0731, 0.7930, 0.2009, ..., 0.5148, 0.9799, 0.9047]) +Matrix: as-caida_G_031 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87232 +Density: 8.859263753197291e-05 +Time: 10.472068786621094 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_032.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_032.json new file mode 100644 index 0000000..380ccf0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_032.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96319, "MATRIX_FILE": "as-caida_G_032", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87938, "MATRIX_DENSITY": 8.930964966166813e-05, "TIME_S": 10.77299976348877, "TIME_S_1KI": 0.11184708898025073, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 761.4244383454323, "W": 72.67, "J_1KI": 7.905236125223812, "W_1KI": 0.7544721186889399, "W_D": 55.91, "J_D": 585.8158847928047, "W_D_1KI": 0.5804669898981509, "J_D_1KI": 0.006026505568975497} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_032.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_032.output new file mode 100644 index 0000000..0388249 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_032.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87938, 87938, 87938]), + col_indices=tensor([ 1809, 21783, 106, ..., 160, 16290, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87938, layout=torch.sparse_csr) +tensor([0.3059, 0.0786, 0.0865, ..., 0.0644, 0.6753, 0.3593]) +Matrix: as-caida_G_032 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87938 +Density: 8.930964966166813e-05 +Time: 10.77299976348877 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_033.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_033.json new file mode 100644 index 0000000..d30e8cb --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_033.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96476, "MATRIX_FILE": "as-caida_G_033", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87784, "MATRIX_DENSITY": 8.915324758238617e-05, "TIME_S": 10.254942893981934, "TIME_S_1KI": 0.10629527441002876, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 756.1478583574295, "W": 72.94, "J_1KI": 7.837678369308735, "W_1KI": 0.7560429536879638, "W_D": 56.636250000000004, "J_D": 587.1316032752395, "W_D_1KI": 0.5870501471868652, "J_D_1KI": 0.00608493456597356} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_033.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_033.output new file mode 100644 index 0000000..d15e873 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_033.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87784, 87784, 87784]), + col_indices=tensor([ 1809, 21783, 106, ..., 160, 16290, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87784, layout=torch.sparse_csr) +tensor([0.6963, 0.6827, 0.0375, ..., 0.7376, 0.1476, 0.5309]) +Matrix: as-caida_G_033 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87784 +Density: 8.915324758238617e-05 +Time: 10.254942893981934 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_034.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_034.json new file mode 100644 index 0000000..197b33a --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_034.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 94001, "MATRIX_FILE": "as-caida_G_034", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88490, "MATRIX_DENSITY": 8.987025971208138e-05, "TIME_S": 10.237717151641846, "TIME_S_1KI": 0.1089107259671902, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 774.7869761466981, "W": 73.2, "J_1KI": 8.242326955529176, "W_1KI": 0.7787151200519145, "W_D": 56.60475, "J_D": 599.1341951918006, "W_D_1KI": 0.6021717854065383, "J_D_1KI": 0.0064060146743815305} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_034.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_034.output new file mode 100644 index 0000000..a456e1e --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_034.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 88489, 88489, 88490]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88490, layout=torch.sparse_csr) +tensor([0.1727, 0.8043, 0.6875, ..., 0.4251, 0.3223, 0.8384]) +Matrix: as-caida_G_034 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88490 +Density: 8.987025971208138e-05 +Time: 10.237717151641846 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_035.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_035.json new file mode 100644 index 0000000..946c7fa --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_035.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98063, "MATRIX_FILE": "as-caida_G_035", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87560, "MATRIX_DENSITY": 8.892575364888514e-05, "TIME_S": 10.373015642166138, "TIME_S_1KI": 0.10577909754103115, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 792.275157444477, "W": 73.19, "J_1KI": 8.079246580713184, "W_1KI": 0.7463569338078582, "W_D": 56.827749999999995, "J_D": 615.1552750166057, "W_D_1KI": 0.5795024627025483, "J_D_1KI": 0.00590949147693369} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_035.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_035.output new file mode 100644 index 0000000..e305dc5 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_035.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 87559, 87559, 87560]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87560, layout=torch.sparse_csr) +tensor([0.6149, 0.9853, 0.7941, ..., 0.7381, 0.6543, 0.7353]) +Matrix: as-caida_G_035 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87560 +Density: 8.892575364888514e-05 +Time: 10.373015642166138 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_036.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_036.json new file mode 100644 index 0000000..707d820 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_036.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 93778, "MATRIX_FILE": "as-caida_G_036", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88616, "MATRIX_DENSITY": 8.999822504967571e-05, "TIME_S": 10.213845252990723, "TIME_S_1KI": 0.10891515337276036, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 721.702276520729, "W": 72.46, "J_1KI": 7.695859119630714, "W_1KI": 0.7726758941329522, "W_D": 56.10274999999999, "J_D": 558.7839138017296, "W_D_1KI": 0.5982506558041331, "J_D_1KI": 0.0063794350039895606} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_036.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_036.output new file mode 100644 index 0000000..5da2ecb --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_036.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 88615, 88615, 88616]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88616, layout=torch.sparse_csr) +tensor([0.3483, 0.2668, 0.1674, ..., 0.7982, 0.1552, 0.7982]) +Matrix: as-caida_G_036 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88616 +Density: 8.999822504967571e-05 +Time: 10.213845252990723 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_037.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_037.json new file mode 100644 index 0000000..d22ed88 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_037.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97905, "MATRIX_FILE": "as-caida_G_037", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88654, "MATRIX_DENSITY": 9.003681777053749e-05, "TIME_S": 10.571146488189697, "TIME_S_1KI": 0.10797350991460801, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 753.6500673270226, "W": 72.53, "J_1KI": 7.697768932404092, "W_1KI": 0.7408201828302947, "W_D": 56.00625, "J_D": 581.9538685128093, "W_D_1KI": 0.5720468821817069, "J_D_1KI": 0.005842877096999202} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_037.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_037.output new file mode 100644 index 0000000..612b139 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_037.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 88653, 88653, 88654]), + col_indices=tensor([ 1809, 106, 329, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88654, layout=torch.sparse_csr) +tensor([0.4083, 0.8283, 0.3104, ..., 0.8903, 0.6247, 0.3838]) +Matrix: as-caida_G_037 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88654 +Density: 9.003681777053749e-05 +Time: 10.571146488189697 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_038.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_038.json new file mode 100644 index 0000000..dedf0d7 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_038.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96984, "MATRIX_FILE": "as-caida_G_038", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88644, "MATRIX_DENSITY": 9.002666179136334e-05, "TIME_S": 10.5276038646698, "TIME_S_1KI": 0.10854990374360514, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 753.529452188015, "W": 72.71, "J_1KI": 7.769626455786676, "W_1KI": 0.7497112925843437, "W_D": 56.4145, "J_D": 584.651179761529, "W_D_1KI": 0.5816887321620061, "J_D_1KI": 0.005997780377814961} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_038.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_038.output new file mode 100644 index 0000000..46f6791 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_038.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 88643, 88643, 88644]), + col_indices=tensor([ 1809, 21783, 106, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88644, layout=torch.sparse_csr) +tensor([0.6608, 0.6516, 0.7484, ..., 0.3860, 0.2912, 0.9376]) +Matrix: as-caida_G_038 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88644 +Density: 9.002666179136334e-05 +Time: 10.5276038646698 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_039.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_039.json new file mode 100644 index 0000000..d0c9ddb --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_039.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99191, "MATRIX_FILE": "as-caida_G_039", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 87804, "MATRIX_DENSITY": 8.917355954073447e-05, "TIME_S": 10.657207727432251, "TIME_S_1KI": 0.10744127720692655, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 778.736130745411, "W": 72.97, "J_1KI": 7.850874885275992, "W_1KI": 0.7356514199877005, "W_D": 50.573, "J_D": 539.7152575056552, "W_D_1KI": 0.5098547247230092, "J_D_1KI": 0.005140130906261749} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_039.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_039.output new file mode 100644 index 0000000..3b098dd --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_039.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 87803, 87803, 87804]), + col_indices=tensor([ 1809, 106, 329, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=87804, layout=torch.sparse_csr) +tensor([0.9679, 0.4863, 0.2440, ..., 0.4590, 0.5364, 0.1027]) +Matrix: as-caida_G_039 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 87804 +Density: 8.917355954073447e-05 +Time: 10.657207727432251 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_040.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_040.json new file mode 100644 index 0000000..4fbd1b0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_040.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95328, "MATRIX_FILE": "as-caida_G_040", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89658, "MATRIX_DENSITY": 9.105647807962247e-05, "TIME_S": 11.115657329559326, "TIME_S_1KI": 0.1166043274752363, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 751.4535146903992, "W": 72.62, "J_1KI": 7.882820521676728, "W_1KI": 0.7617908694192683, "W_D": 56.248000000000005, "J_D": 582.0401720504761, "W_D_1KI": 0.5900469956361195, "J_D_1KI": 0.00618965042417883} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_040.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_040.output new file mode 100644 index 0000000..db3c417 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_040.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89657, 89657, 89658]), + col_indices=tensor([ 106, 329, 1040, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89658, layout=torch.sparse_csr) +tensor([0.3995, 0.4922, 0.3108, ..., 0.9056, 0.8978, 0.2437]) +Matrix: as-caida_G_040 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89658 +Density: 9.105647807962247e-05 +Time: 11.115657329559326 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_041.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_041.json new file mode 100644 index 0000000..5b58955 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_041.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97826, "MATRIX_FILE": "as-caida_G_041", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 88944, "MATRIX_DENSITY": 9.033134116658794e-05, "TIME_S": 10.71406602859497, "TIME_S_1KI": 0.10952166120044743, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 780.3498594760895, "W": 72.75, "J_1KI": 7.97691676523715, "W_1KI": 0.7436673277042912, "W_D": 56.397999999999996, "J_D": 604.9508092746735, "W_D_1KI": 0.5765134013452456, "J_D_1KI": 0.005893253341087703} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_041.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_041.output new file mode 100644 index 0000000..45368b8 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_041.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 88943, 88943, 88944]), + col_indices=tensor([ 106, 329, 1040, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=88944, layout=torch.sparse_csr) +tensor([0.6903, 0.3159, 0.0760, ..., 0.8554, 0.7274, 0.6040]) +Matrix: as-caida_G_041 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 88944 +Density: 9.033134116658794e-05 +Time: 10.71406602859497 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_042.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_042.json new file mode 100644 index 0000000..bd2e603 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_042.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98794, "MATRIX_FILE": "as-caida_G_042", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89176, "MATRIX_DENSITY": 9.056695988342829e-05, "TIME_S": 10.580000400543213, "TIME_S_1KI": 0.1070915278310749, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 769.2550509738923, "W": 72.84, "J_1KI": 7.786455158955931, "W_1KI": 0.7372917383646781, "W_D": 56.38525, "J_D": 595.4782861467004, "W_D_1KI": 0.5707355709860922, "J_D_1KI": 0.005777026651275302} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_042.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_042.output new file mode 100644 index 0000000..ddba12d --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_042.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89173, 89173, 89176]), + col_indices=tensor([ 106, 329, 1040, ..., 2232, 5295, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 3.]), size=(31379, 31379), + nnz=89176, layout=torch.sparse_csr) +tensor([0.3192, 0.6280, 0.4871, ..., 0.9053, 0.8616, 0.2002]) +Matrix: as-caida_G_042 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89176 +Density: 9.056695988342829e-05 +Time: 10.580000400543213 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_043.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_043.json new file mode 100644 index 0000000..432c377 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_043.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96445, "MATRIX_FILE": "as-caida_G_043", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89678, "MATRIX_DENSITY": 9.107679003797077e-05, "TIME_S": 10.58508014678955, "TIME_S_1KI": 0.10975250294768574, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 767.899575343132, "W": 73.03, "J_1KI": 7.9620465067461454, "W_1KI": 0.7572191404427394, "W_D": 56.66975, "J_D": 595.8739827440977, "W_D_1KI": 0.5875861890196485, "J_D_1KI": 0.006092448431952393} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_043.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_043.output new file mode 100644 index 0000000..8319376 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_043.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89676, 89676, 89678]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89678, layout=torch.sparse_csr) +tensor([0.3015, 0.9723, 0.8451, ..., 0.4828, 0.0936, 0.2431]) +Matrix: as-caida_G_043 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89678 +Density: 9.107679003797077e-05 +Time: 10.58508014678955 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_044.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_044.json new file mode 100644 index 0000000..246470d --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_044.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97785, "MATRIX_FILE": "as-caida_G_044", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89560, "MATRIX_DENSITY": 9.095694948371577e-05, "TIME_S": 10.568169355392456, "TIME_S_1KI": 0.10807556737119656, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 760.5352007484437, "W": 72.76, "J_1KI": 7.777626432974829, "W_1KI": 0.7440814030781818, "W_D": 55.90700000000001, "J_D": 584.3766007180215, "W_D_1KI": 0.5717339060183055, "J_D_1KI": 0.0058468467149185} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_044.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_044.output new file mode 100644 index 0000000..f49395d --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_044.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 89559, 89559, 89560]), + col_indices=tensor([ 5326, 106, 329, ..., 10144, 882, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89560, layout=torch.sparse_csr) +tensor([0.6824, 0.8411, 0.7953, ..., 0.6576, 0.0308, 0.0827]) +Matrix: as-caida_G_044 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89560 +Density: 9.095694948371577e-05 +Time: 10.568169355392456 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_045.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_045.json new file mode 100644 index 0000000..8287fd2 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_045.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96286, "MATRIX_FILE": "as-caida_G_045", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 89152, "MATRIX_DENSITY": 9.054258553341032e-05, "TIME_S": 10.446382999420166, "TIME_S_1KI": 0.10849327004362178, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 767.4934634971619, "W": 73.04, "J_1KI": 7.970976709980287, "W_1KI": 0.7585734166960929, "W_D": 56.45550000000001, "J_D": 593.2260025802851, "W_D_1KI": 0.5863313461977858, "J_D_1KI": 0.006089476623785242} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_045.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_045.output new file mode 100644 index 0000000..4dc4353 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_045.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 89150, 89150, 89152]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=89152, layout=torch.sparse_csr) +tensor([0.2083, 0.9903, 0.1196, ..., 0.8506, 0.4574, 0.4287]) +Matrix: as-caida_G_045 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 89152 +Density: 9.054258553341032e-05 +Time: 10.446382999420166 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_046.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_046.json new file mode 100644 index 0000000..ce1dab0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_046.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96302, "MATRIX_FILE": "as-caida_G_046", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90172, "MATRIX_DENSITY": 9.157849540917394e-05, "TIME_S": 10.442455530166626, "TIME_S_1KI": 0.10843446169515301, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 767.8247145581246, "W": 72.93, "J_1KI": 7.973092091110512, "W_1KI": 0.7573051442337647, "W_D": 56.26825000000001, "J_D": 592.4057725892663, "W_D_1KI": 0.584289526697265, "J_D_1KI": 0.0060672626393768045} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_046.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_046.output new file mode 100644 index 0000000..cafb51e --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_046.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 90170, 90170, 90172]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90172, layout=torch.sparse_csr) +tensor([0.2952, 0.2268, 0.9557, ..., 0.6413, 0.2854, 0.6377]) +Matrix: as-caida_G_046 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90172 +Density: 9.157849540917394e-05 +Time: 10.442455530166626 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_047.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_047.json new file mode 100644 index 0000000..b1cb77e --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_047.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 94324, "MATRIX_FILE": "as-caida_G_047", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90002, "MATRIX_DENSITY": 9.140584376321335e-05, "TIME_S": 10.391080141067505, "TIME_S_1KI": 0.11016369260281057, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 750.4909230041504, "W": 72.68, "J_1KI": 7.956521383785149, "W_1KI": 0.7705356006954753, "W_D": 56.00000000000001, "J_D": 578.253875732422, "W_D_1KI": 0.5936983164412027, "J_D_1KI": 0.00629424448116283} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_047.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_047.output new file mode 100644 index 0000000..db886b8 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_047.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90000, 90000, 90002]), + col_indices=tensor([ 5326, 106, 329, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90002, layout=torch.sparse_csr) +tensor([0.5794, 0.3907, 0.6950, ..., 0.6784, 0.6821, 0.7067]) +Matrix: as-caida_G_047 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90002 +Density: 9.140584376321335e-05 +Time: 10.391080141067505 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_048.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_048.json new file mode 100644 index 0000000..0e141d2 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_048.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96455, "MATRIX_FILE": "as-caida_G_048", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90820, "MATRIX_DENSITY": 9.223660285965907e-05, "TIME_S": 10.492300271987915, "TIME_S_1KI": 0.108779226291928, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 758.1999660515785, "W": 72.53, "J_1KI": 7.860660059629655, "W_1KI": 0.7519568710797782, "W_D": 56.11325, "J_D": 586.5857472086549, "W_D_1KI": 0.5817557410191281, "J_D_1KI": 0.006031369457458173} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_048.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_048.output new file mode 100644 index 0000000..0701092 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_048.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 90816, 90816, 90820]), + col_indices=tensor([ 106, 329, 1040, ..., 3562, 13498, 16085]), + values=tensor([1., 1., 1., ..., 3., 3., 3.]), size=(31379, 31379), + nnz=90820, layout=torch.sparse_csr) +tensor([0.4616, 0.4022, 0.7655, ..., 0.7387, 0.9419, 0.0764]) +Matrix: as-caida_G_048 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90820 +Density: 9.223660285965907e-05 +Time: 10.492300271987915 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_049.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_049.json new file mode 100644 index 0000000..f62f56e --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_049.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95067, "MATRIX_FILE": "as-caida_G_049", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90784, "MATRIX_DENSITY": 9.220004133463212e-05, "TIME_S": 10.192533254623413, "TIME_S_1KI": 0.10721420950091422, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 745.3328839492797, "W": 72.82, "J_1KI": 7.840079985160777, "W_1KI": 0.7659860940179032, "W_D": 56.388749999999995, "J_D": 577.1544858527183, "W_D_1KI": 0.5931474644198302, "J_D_1KI": 0.006239257201971559} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_049.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_049.output new file mode 100644 index 0000000..87bb78c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_049.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90780, 90780, 90784]), + col_indices=tensor([ 5326, 106, 329, ..., 3562, 13498, 16085]), + values=tensor([1., 1., 1., ..., 3., 3., 3.]), size=(31379, 31379), + nnz=90784, layout=torch.sparse_csr) +tensor([0.2853, 0.3316, 0.4007, ..., 0.1551, 0.1099, 0.1414]) +Matrix: as-caida_G_049 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90784 +Density: 9.220004133463212e-05 +Time: 10.192533254623413 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_050.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_050.json new file mode 100644 index 0000000..49a74da --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_050.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97582, "MATRIX_FILE": "as-caida_G_050", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90392, "MATRIX_DENSITY": 9.180192695100532e-05, "TIME_S": 10.443605184555054, "TIME_S_1KI": 0.10702388949350346, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 782.8872513103485, "W": 73.16, "J_1KI": 8.022865398437709, "W_1KI": 0.7497284335225759, "W_D": 56.632, "J_D": 606.020650850296, "W_D_1KI": 0.5803529339427353, "J_D_1KI": 0.0059473359220218415} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_050.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_050.output new file mode 100644 index 0000000..04dceb7 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_050.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90390, 90390, 90392]), + col_indices=tensor([ 5326, 106, 329, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90392, layout=torch.sparse_csr) +tensor([0.7242, 0.1307, 0.4994, ..., 0.6857, 0.9727, 0.2547]) +Matrix: as-caida_G_050 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90392 +Density: 9.180192695100532e-05 +Time: 10.443605184555054 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_051.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_051.json new file mode 100644 index 0000000..95b2af0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_051.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96021, "MATRIX_FILE": "as-caida_G_051", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90100, "MATRIX_DENSITY": 9.150537235912004e-05, "TIME_S": 10.32409930229187, "TIME_S_1KI": 0.10751918124464305, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 746.418474111557, "W": 72.77, "J_1KI": 7.773491987289832, "W_1KI": 0.75785505254059, "W_D": 55.92249999999999, "J_D": 573.6098271059989, "W_D_1KI": 0.582398641963737, "J_D_1KI": 0.006065325730452057} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_051.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_051.output new file mode 100644 index 0000000..9679270 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_051.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90098, 90098, 90100]), + col_indices=tensor([ 5326, 106, 329, ..., 882, 2232, 16085]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90100, layout=torch.sparse_csr) +tensor([0.5266, 0.0316, 0.4877, ..., 0.8893, 0.1889, 0.3286]) +Matrix: as-caida_G_051 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90100 +Density: 9.150537235912004e-05 +Time: 10.32409930229187 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_052.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_052.json new file mode 100644 index 0000000..64e4174 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_052.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95838, "MATRIX_FILE": "as-caida_G_052", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 91100, "MATRIX_DENSITY": 9.252097027653536e-05, "TIME_S": 10.47776746749878, "TIME_S_1KI": 0.10932790195432687, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 749.9839658546448, "W": 72.72, "J_1KI": 7.825538573996168, "W_1KI": 0.758780441995868, "W_D": 56.32325, "J_D": 580.8791859849096, "W_D_1KI": 0.5876922515077527, "J_D_1KI": 0.006132142276630906} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_052.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_052.output new file mode 100644 index 0000000..3cc406c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_052.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 91097, 91097, 91100]), + col_indices=tensor([ 106, 329, 1040, ..., 2232, 16085, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=91100, layout=torch.sparse_csr) +tensor([0.6938, 0.0946, 0.1504, ..., 0.2517, 0.4329, 0.0396]) +Matrix: as-caida_G_052 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 91100 +Density: 9.252097027653536e-05 +Time: 10.47776746749878 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_053.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_053.json new file mode 100644 index 0000000..ba02dc1 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_053.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97864, "MATRIX_FILE": "as-caida_G_053", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 90296, "MATRIX_DENSITY": 9.170442955093344e-05, "TIME_S": 10.594428062438965, "TIME_S_1KI": 0.1082566425083684, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 765.8935358452796, "W": 72.91, "J_1KI": 7.826100873102261, "W_1KI": 0.7450134881059429, "W_D": 56.39975, "J_D": 592.4592504222989, "W_D_1KI": 0.5763074266328783, "J_D_1KI": 0.00588886032282431} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_053.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_053.output new file mode 100644 index 0000000..33428ee --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_053.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 90294, 90294, 90296]), + col_indices=tensor([21783, 106, 329, ..., 160, 16085, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=90296, layout=torch.sparse_csr) +tensor([0.4150, 0.5213, 0.3237, ..., 0.5706, 0.3908, 0.8117]) +Matrix: as-caida_G_053 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 90296 +Density: 9.170442955093344e-05 +Time: 10.594428062438965 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_054.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_054.json new file mode 100644 index 0000000..0abc805 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_054.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95499, "MATRIX_FILE": "as-caida_G_054", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92170, "MATRIX_DENSITY": 9.360766004816975e-05, "TIME_S": 10.340025186538696, "TIME_S_1KI": 0.1082736487977748, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 754.2966740226746, "W": 72.72, "J_1KI": 7.898477198951555, "W_1KI": 0.7614739421355197, "W_D": 56.277249999999995, "J_D": 583.7423335828184, "W_D_1KI": 0.5892967465627912, "J_D_1KI": 0.006170711175643632} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_054.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_054.output new file mode 100644 index 0000000..0159299 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_054.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 92169, 92169, 92170]), + col_indices=tensor([21783, 106, 329, ..., 155, 160, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92170, layout=torch.sparse_csr) +tensor([0.3994, 0.3258, 0.3211, ..., 0.6360, 0.6829, 0.0308]) +Matrix: as-caida_G_054 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92170 +Density: 9.360766004816975e-05 +Time: 10.340025186538696 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_055.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_055.json new file mode 100644 index 0000000..3dc1ec4 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_055.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96776, "MATRIX_FILE": "as-caida_G_055", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 91476, "MATRIX_DENSITY": 9.290283509348351e-05, "TIME_S": 10.79194974899292, "TIME_S_1KI": 0.1115147324645875, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 766.135677909851, "W": 72.66, "J_1KI": 7.916587562100634, "W_1KI": 0.7508059849549474, "W_D": 50.3915, "J_D": 531.3339666032791, "W_D_1KI": 0.5207024468876581, "J_D_1KI": 0.005380491515330848} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_055.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_055.output new file mode 100644 index 0000000..295cba0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_055.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 91475, 91475, 91476]), + col_indices=tensor([21783, 106, 329, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=91476, layout=torch.sparse_csr) +tensor([0.5088, 0.7409, 0.7048, ..., 0.7527, 0.1952, 0.8421]) +Matrix: as-caida_G_055 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 91476 +Density: 9.290283509348351e-05 +Time: 10.79194974899292 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_056.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_056.json new file mode 100644 index 0000000..d1bde4d --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_056.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 93750, "MATRIX_FILE": "as-caida_G_056", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92826, "MATRIX_DENSITY": 9.427389228199419e-05, "TIME_S": 10.300837993621826, "TIME_S_1KI": 0.10987560526529948, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 755.6952035903931, "W": 72.67, "J_1KI": 8.060748838297526, "W_1KI": 0.7751466666666667, "W_D": 56.322, "J_D": 585.692380027771, "W_D_1KI": 0.600768, "J_D_1KI": 0.006408192} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_056.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_056.output new file mode 100644 index 0000000..cb6f13b --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_056.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 92825, 92825, 92826]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92826, layout=torch.sparse_csr) +tensor([0.7040, 0.1453, 0.6707, ..., 0.8370, 0.5551, 0.2045]) +Matrix: as-caida_G_056 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92826 +Density: 9.427389228199419e-05 +Time: 10.300837993621826 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_057.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_057.json new file mode 100644 index 0000000..3c54343 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_057.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95574, "MATRIX_FILE": "as-caida_G_057", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92334, "MATRIX_DENSITY": 9.377421810662586e-05, "TIME_S": 10.358325958251953, "TIME_S_1KI": 0.10838016571716108, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 779.1045169520378, "W": 72.91, "J_1KI": 8.151845867621295, "W_1KI": 0.7628643773411178, "W_D": 56.546749999999996, "J_D": 604.2494629537463, "W_D_1KI": 0.5916541109506769, "J_D_1KI": 0.006190534151031419} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_057.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_057.output new file mode 100644 index 0000000..5645650 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_057.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 92333, 92333, 92334]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92334, layout=torch.sparse_csr) +tensor([0.5990, 0.2032, 0.4589, ..., 0.9199, 0.1616, 0.1636]) +Matrix: as-caida_G_057 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92334 +Density: 9.377421810662586e-05 +Time: 10.358325958251953 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_058.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_058.json new file mode 100644 index 0000000..1b783ce --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_058.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95965, "MATRIX_FILE": "as-caida_G_058", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92170, "MATRIX_DENSITY": 9.360766004816975e-05, "TIME_S": 10.50449538230896, "TIME_S_1KI": 0.10946173482320597, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 761.0065832757949, "W": 72.74, "J_1KI": 7.930043070659043, "W_1KI": 0.7579846819152816, "W_D": 56.38699999999999, "J_D": 589.9213391692638, "W_D_1KI": 0.5875788047725733, "J_D_1KI": 0.006122844836894423} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_058.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_058.output new file mode 100644 index 0000000..36de63c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_058.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 92169, 92169, 92170]), + col_indices=tensor([ 996, 25003, 106, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92170, layout=torch.sparse_csr) +tensor([0.3198, 0.7966, 0.2031, ..., 0.1136, 0.4855, 0.4004]) +Matrix: as-caida_G_058 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92170 +Density: 9.360766004816975e-05 +Time: 10.50449538230896 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_059.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_059.json new file mode 100644 index 0000000..d97b07c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_059.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95471, "MATRIX_FILE": "as-caida_G_059", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93156, "MATRIX_DENSITY": 9.460903959474125e-05, "TIME_S": 10.46764588356018, "TIME_S_1KI": 0.10964215189492287, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 754.9866472196578, "W": 72.46, "J_1KI": 7.908020731108481, "W_1KI": 0.7589739292560044, "W_D": 55.84049999999999, "J_D": 581.8221346131562, "W_D_1KI": 0.5848948895476113, "J_D_1KI": 0.006126414194337665} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_059.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_059.output new file mode 100644 index 0000000..677afa7 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_059.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 2, 2, ..., 93155, 93155, 93156]), + col_indices=tensor([ 996, 25003, 106, ..., 160, 882, 17255]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93156, layout=torch.sparse_csr) +tensor([0.6388, 0.2678, 0.5457, ..., 0.9208, 0.1288, 0.2987]) +Matrix: as-caida_G_059 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93156 +Density: 9.460903959474125e-05 +Time: 10.46764588356018 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_060.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_060.json new file mode 100644 index 0000000..d55ab22 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_060.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96700, "MATRIX_FILE": "as-caida_G_060", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94180, "MATRIX_DENSITY": 9.564901186217454e-05, "TIME_S": 10.476623773574829, "TIME_S_1KI": 0.10834150748267662, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 927.6598570609093, "W": 73.73, "J_1KI": 9.593173289151078, "W_1KI": 0.7624612202688729, "W_D": 57.19975, "J_D": 719.6787184174657, "W_D_1KI": 0.5915175801447776, "J_D_1KI": 0.006117038057339996} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_060.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_060.output new file mode 100644 index 0000000..a018079 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_060.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94180, 94180, 94180]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94180, layout=torch.sparse_csr) +tensor([0.3042, 0.8353, 0.3052, ..., 0.8747, 0.0607, 0.6967]) +Matrix: as-caida_G_060 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94180 +Density: 9.564901186217454e-05 +Time: 10.476623773574829 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_061.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_061.json new file mode 100644 index 0000000..735dde7 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_061.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 94364, "MATRIX_FILE": "as-caida_G_061", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94386, "MATRIX_DENSITY": 9.58582250331621e-05, "TIME_S": 10.526966333389282, "TIME_S_1KI": 0.11155701680078506, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 775.4535556006431, "W": 72.83, "J_1KI": 8.217684239759262, "W_1KI": 0.7717985672502226, "W_D": 56.60325, "J_D": 602.6800970898271, "W_D_1KI": 0.599839451485736, "J_D_1KI": 0.00635665562593506} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_061.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_061.output new file mode 100644 index 0000000..0e38784 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_061.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94386, 94386, 94386]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94386, layout=torch.sparse_csr) +tensor([0.7604, 0.5644, 0.0413, ..., 0.1855, 0.3260, 0.9560]) +Matrix: as-caida_G_061 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94386 +Density: 9.58582250331621e-05 +Time: 10.526966333389282 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_062.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_062.json new file mode 100644 index 0000000..351e2ce --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_062.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95088, "MATRIX_FILE": "as-caida_G_062", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93728, "MATRIX_DENSITY": 9.518996160350281e-05, "TIME_S": 10.29589056968689, "TIME_S_1KI": 0.10827749631590622, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 747.0692161917686, "W": 72.75, "J_1KI": 7.856608785459455, "W_1KI": 0.7650807672892479, "W_D": 55.96075, "J_D": 574.660531134069, "W_D_1KI": 0.5885153752313645, "J_D_1KI": 0.006189165564859546} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_062.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_062.output new file mode 100644 index 0000000..382d169 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_062.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93728, 93728, 93728]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93728, layout=torch.sparse_csr) +tensor([0.5005, 0.0958, 0.7394, ..., 0.5369, 0.3540, 0.4417]) +Matrix: as-caida_G_062 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93728 +Density: 9.518996160350281e-05 +Time: 10.29589056968689 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_063.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_063.json new file mode 100644 index 0000000..678e927 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_063.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97877, "MATRIX_FILE": "as-caida_G_063", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94736, "MATRIX_DENSITY": 9.621368430425745e-05, "TIME_S": 10.692056894302368, "TIME_S_1KI": 0.10923972837645585, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 774.8052859210968, "W": 72.84, "J_1KI": 7.9161119151700285, "W_1KI": 0.74419935224823, "W_D": 56.2625, "J_D": 598.4690060287714, "W_D_1KI": 0.5748286114204564, "J_D_1KI": 0.005872969251412042} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_063.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_063.output new file mode 100644 index 0000000..4634edf --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_063.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94736, 94736, 94736]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94736, layout=torch.sparse_csr) +tensor([0.7634, 0.5606, 0.6689, ..., 0.6917, 0.4756, 0.1246]) +Matrix: as-caida_G_063 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94736 +Density: 9.621368430425745e-05 +Time: 10.692056894302368 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_064.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_064.json new file mode 100644 index 0000000..47f0407 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_064.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95795, "MATRIX_FILE": "as-caida_G_064", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93558, "MATRIX_DENSITY": 9.50173099575422e-05, "TIME_S": 10.645073652267456, "TIME_S_1KI": 0.11112347880648735, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 799.8198983430863, "W": 72.62, "J_1KI": 8.349286479911125, "W_1KI": 0.7580771439010388, "W_D": 55.947250000000004, "J_D": 616.1900827261805, "W_D_1KI": 0.5840310037058302, "J_D_1KI": 0.006096675230500863} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_064.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_064.output new file mode 100644 index 0000000..e1c409d --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_064.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93558, 93558, 93558]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93558, layout=torch.sparse_csr) +tensor([0.6723, 0.2191, 0.9180, ..., 0.7506, 0.4189, 0.9529]) +Matrix: as-caida_G_064 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93558 +Density: 9.50173099575422e-05 +Time: 10.645073652267456 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_065.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_065.json new file mode 100644 index 0000000..a04944a --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_065.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 92948, "MATRIX_FILE": "as-caida_G_065", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 95068, "MATRIX_DENSITY": 9.655086281283934e-05, "TIME_S": 10.279686689376831, "TIME_S_1KI": 0.11059610415906562, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 753.1111097335815, "W": 72.16, "J_1KI": 8.102499351611456, "W_1KI": 0.7763480655850583, "W_D": 55.7675, "J_D": 582.0277690142393, "W_D_1KI": 0.5999860136850712, "J_D_1KI": 0.0064550718002008775} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_065.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_065.output new file mode 100644 index 0000000..c0a2f3b --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_065.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 95068, 95068, 95068]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=95068, layout=torch.sparse_csr) +tensor([0.3470, 0.2796, 0.4349, ..., 0.3018, 0.6693, 0.1601]) +Matrix: as-caida_G_065 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 95068 +Density: 9.655086281283934e-05 +Time: 10.279686689376831 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_066.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_066.json new file mode 100644 index 0000000..22a5639 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_066.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96119, "MATRIX_FILE": "as-caida_G_066", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93212, "MATRIX_DENSITY": 9.466591307811651e-05, "TIME_S": 10.503400802612305, "TIME_S_1KI": 0.10927496959614962, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 789.1941960024834, "W": 72.79, "J_1KI": 8.210595158111127, "W_1KI": 0.7572904420562012, "W_D": 56.438500000000005, "J_D": 611.9101062108278, "W_D_1KI": 0.5871731915646231, "J_D_1KI": 0.006108815026837806} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_066.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_066.output new file mode 100644 index 0000000..0323588 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_066.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93212, 93212, 93212]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93212, layout=torch.sparse_csr) +tensor([0.5653, 0.6470, 0.9251, ..., 0.1641, 0.5738, 0.8712]) +Matrix: as-caida_G_066 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93212 +Density: 9.466591307811651e-05 +Time: 10.503400802612305 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_067.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_067.json new file mode 100644 index 0000000..6ada284 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_067.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96463, "MATRIX_FILE": "as-caida_G_067", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 94484, "MATRIX_DENSITY": 9.59577536290688e-05, "TIME_S": 10.647246599197388, "TIME_S_1KI": 0.11037648216619209, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 762.5915017247199, "W": 72.63, "J_1KI": 7.905533745837471, "W_1KI": 0.7529311756839409, "W_D": 55.964999999999996, "J_D": 587.6143934190272, "W_D_1KI": 0.5801706353731482, "J_D_1KI": 0.006014436990070268} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_067.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_067.output new file mode 100644 index 0000000..ea567cd --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_067.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 94484, 94484, 94484]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=94484, layout=torch.sparse_csr) +tensor([0.1329, 0.4672, 0.2260, ..., 0.3245, 0.2819, 0.8090]) +Matrix: as-caida_G_067 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 94484 +Density: 9.59577536290688e-05 +Time: 10.647246599197388 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_068.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_068.json new file mode 100644 index 0000000..7f9328f --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_068.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95879, "MATRIX_FILE": "as-caida_G_068", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 93310, "MATRIX_DENSITY": 9.47654416740232e-05, "TIME_S": 10.410168647766113, "TIME_S_1KI": 0.10857610788354188, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 756.2592768287658, "W": 72.66, "J_1KI": 7.8876425163880075, "W_1KI": 0.7578301817916332, "W_D": 56.23325, "J_D": 585.2864984686374, "W_D_1KI": 0.5865022580544227, "J_D_1KI": 0.0061171086270656} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_068.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_068.output new file mode 100644 index 0000000..f2e841c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_068.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 93310, 93310, 93310]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 882]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=93310, layout=torch.sparse_csr) +tensor([0.6963, 0.6478, 0.5901, ..., 0.1045, 0.2159, 0.6527]) +Matrix: as-caida_G_068 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 93310 +Density: 9.47654416740232e-05 +Time: 10.410168647766113 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_069.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_069.json new file mode 100644 index 0000000..4bccb7f --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_069.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96797, "MATRIX_FILE": "as-caida_G_069", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 92190, "MATRIX_DENSITY": 9.362797200651806e-05, "TIME_S": 10.649985790252686, "TIME_S_1KI": 0.11002392419447592, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 774.0189748764038, "W": 72.55, "J_1KI": 7.9963116096201725, "W_1KI": 0.7495066995877971, "W_D": 56.2155, "J_D": 599.7500162944793, "W_D_1KI": 0.5807566350196803, "J_D_1KI": 0.005999737956958173} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_069.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_069.output new file mode 100644 index 0000000..94753eb --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_069.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 92190, 92190, 92190]), + col_indices=tensor([ 106, 329, 1040, ..., 978, 19739, 160]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=92190, layout=torch.sparse_csr) +tensor([0.5175, 0.8264, 0.4051, ..., 0.3261, 0.7154, 0.2791]) +Matrix: as-caida_G_069 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 92190 +Density: 9.362797200651806e-05 +Time: 10.649985790252686 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_070.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_070.json new file mode 100644 index 0000000..79341f9 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_070.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 100518, "MATRIX_FILE": "as-caida_G_070", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 78684, "MATRIX_DENSITY": 7.991130653390679e-05, "TIME_S": 10.531989574432373, "TIME_S_1KI": 0.10477715010677066, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 764.0369100546836, "W": 72.61, "J_1KI": 7.600995941569507, "W_1KI": 0.7223581846037526, "W_D": 56.07025, "J_D": 589.9978041040301, "W_D_1KI": 0.5578130285123062, "J_D_1KI": 0.0055493844735500725} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_070.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_070.output new file mode 100644 index 0000000..bb0a520 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_070.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 78684, 78684, 78684]), + col_indices=tensor([ 106, 329, 1040, ..., 16263, 2242, 2242]), + values=tensor([1., 1., 1., ..., 3., 1., 1.]), size=(31379, 31379), + nnz=78684, layout=torch.sparse_csr) +tensor([0.8678, 0.6451, 0.4027, ..., 0.3009, 0.5441, 0.8741]) +Matrix: as-caida_G_070 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 78684 +Density: 7.991130653390679e-05 +Time: 10.531989574432373 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_071.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_071.json new file mode 100644 index 0000000..2baf7f3 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_071.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96685, "MATRIX_FILE": "as-caida_G_071", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 96012, "MATRIX_DENSITY": 9.75095872468794e-05, "TIME_S": 10.739191055297852, "TIME_S_1KI": 0.11107401412109273, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 768.2110359477997, "W": 72.62, "J_1KI": 7.9455038108062235, "W_1KI": 0.7510989295133682, "W_D": 56.04600000000001, "J_D": 592.8828934278489, "W_D_1KI": 0.5796762682939444, "J_D_1KI": 0.0059955139710807705} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_071.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_071.output new file mode 100644 index 0000000..7bb11c5 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_071.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 96011, 96011, 96012]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=96012, layout=torch.sparse_csr) +tensor([0.6415, 0.4658, 0.4601, ..., 0.0352, 0.4969, 0.5275]) +Matrix: as-caida_G_071 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 96012 +Density: 9.75095872468794e-05 +Time: 10.739191055297852 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_072.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_072.json new file mode 100644 index 0000000..1c2582b --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_072.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95961, "MATRIX_FILE": "as-caida_G_072", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 96404, "MATRIX_DENSITY": 9.79077016305062e-05, "TIME_S": 10.456534385681152, "TIME_S_1KI": 0.10896650082513888, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 760.8548632526397, "W": 72.52, "J_1KI": 7.9287925641942, "W_1KI": 0.7557236794114275, "W_D": 55.98049999999999, "J_D": 587.3281256524324, "W_D_1KI": 0.5833672012588447, "J_D_1KI": 0.006079211359394386} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_072.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_072.output new file mode 100644 index 0000000..99b0e7a --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_072.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 96403, 96403, 96404]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=96404, layout=torch.sparse_csr) +tensor([0.8664, 0.5641, 0.1950, ..., 0.7900, 0.7074, 0.9899]) +Matrix: as-caida_G_072 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 96404 +Density: 9.79077016305062e-05 +Time: 10.456534385681152 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_073.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_073.json new file mode 100644 index 0000000..cfdb486 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_073.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96053, "MATRIX_FILE": "as-caida_G_073", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 95554, "MATRIX_DENSITY": 9.704444340070319e-05, "TIME_S": 10.662086486816406, "TIME_S_1KI": 0.11100211848475744, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 792.4175423121452, "W": 73.03, "J_1KI": 8.249794824858622, "W_1KI": 0.7603094125118425, "W_D": 56.564, "J_D": 613.7519630746841, "W_D_1KI": 0.5888832207218931, "J_D_1KI": 0.006130815494798634} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_073.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_073.output new file mode 100644 index 0000000..cf2b6b1 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_073.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 95553, 95553, 95554]), + col_indices=tensor([22754, 22754, 106, ..., 978, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=95554, layout=torch.sparse_csr) +tensor([0.8601, 0.3473, 0.0052, ..., 0.2790, 0.5514, 0.6735]) +Matrix: as-caida_G_073 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 95554 +Density: 9.704444340070319e-05 +Time: 10.662086486816406 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_074.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_074.json new file mode 100644 index 0000000..6b70192 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_074.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 93430, "MATRIX_FILE": "as-caida_G_074", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 97296, "MATRIX_DENSITY": 9.881361497284067e-05, "TIME_S": 10.428792953491211, "TIME_S_1KI": 0.11162145941872215, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 749.3437918186188, "W": 72.86, "J_1KI": 8.02037666508208, "W_1KI": 0.779835170716044, "W_D": 56.4995, "J_D": 581.0808340084552, "W_D_1KI": 0.6047254629134111, "J_D_1KI": 0.0064724977299947676} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_074.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_074.output new file mode 100644 index 0000000..5f62b24 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_074.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 97295, 97295, 97296]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=97296, layout=torch.sparse_csr) +tensor([0.4530, 0.6338, 0.7552, ..., 0.0496, 0.3433, 0.1746]) +Matrix: as-caida_G_074 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 97296 +Density: 9.881361497284067e-05 +Time: 10.428792953491211 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_075.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_075.json new file mode 100644 index 0000000..513836d --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_075.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95603, "MATRIX_FILE": "as-caida_G_075", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 97492, "MATRIX_DENSITY": 9.901267216465406e-05, "TIME_S": 10.648608446121216, "TIME_S_1KI": 0.11138362233529508, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 762.7721357345581, "W": 72.72, "J_1KI": 7.97853765817556, "W_1KI": 0.7606455864355721, "W_D": 56.2025, "J_D": 589.5173399150372, "W_D_1KI": 0.5878738114912713, "J_D_1KI": 0.006149114687732302} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_075.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_075.output new file mode 100644 index 0000000..e4a93f2 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_075.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 97491, 97491, 97492]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=97492, layout=torch.sparse_csr) +tensor([0.6673, 0.5090, 0.3501, ..., 0.7852, 0.0871, 0.7446]) +Matrix: as-caida_G_075 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 97492 +Density: 9.901267216465406e-05 +Time: 10.648608446121216 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_076.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_076.json new file mode 100644 index 0000000..6f1ad11 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_076.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 93112, "MATRIX_FILE": "as-caida_G_076", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98178, "MATRIX_DENSITY": 9.970937233600097e-05, "TIME_S": 10.525174617767334, "TIME_S_1KI": 0.11303778909020679, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 765.899048910141, "W": 72.36, "J_1KI": 8.225567584308585, "W_1KI": 0.7771286192971905, "W_D": 55.973749999999995, "J_D": 592.4577375474572, "W_D_1KI": 0.6011443208179397, "J_D_1KI": 0.006456142289049099} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_076.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_076.output new file mode 100644 index 0000000..5c9df26 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_076.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98177, 98177, 98178]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98178, layout=torch.sparse_csr) +tensor([0.0801, 0.3615, 0.1072, ..., 0.6647, 0.9006, 0.2089]) +Matrix: as-caida_G_076 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98178 +Density: 9.970937233600097e-05 +Time: 10.525174617767334 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_077.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_077.json new file mode 100644 index 0000000..09aba2b --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_077.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 99252, "MATRIX_FILE": "as-caida_G_077", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98664, "MATRIX_DENSITY": 0.00010020295292386482, "TIME_S": 10.682153224945068, "TIME_S_1KI": 0.10762657906082566, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 776.9801347351074, "W": 72.64, "J_1KI": 7.8283574611605555, "W_1KI": 0.731874420666586, "W_D": 56.2665, "J_D": 601.8440632030964, "W_D_1KI": 0.5669054527868456, "J_D_1KI": 0.005711778632036086} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_077.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_077.output new file mode 100644 index 0000000..d601d78 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_077.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98663, 98663, 98664]), + col_indices=tensor([22754, 22754, 106, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98664, layout=torch.sparse_csr) +tensor([0.5993, 0.5020, 0.6001, ..., 0.1216, 0.8683, 0.4295]) +Matrix: as-caida_G_077 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98664 +Density: 0.00010020295292386482 +Time: 10.682153224945068 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_078.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_078.json new file mode 100644 index 0000000..9f05dcc --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_078.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98586, "MATRIX_FILE": "as-caida_G_078", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98782, "MATRIX_DENSITY": 0.00010032279347811982, "TIME_S": 10.51060438156128, "TIME_S_1KI": 0.10661355954761609, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 763.3612938165666, "W": 72.79, "J_1KI": 7.743100377503566, "W_1KI": 0.7383401294301423, "W_D": 56.331500000000005, "J_D": 590.7581635200978, "W_D_1KI": 0.5713945184914694, "J_D_1KI": 0.005795899199596995} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_078.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_078.output new file mode 100644 index 0000000..3264ae4 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_078.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98781, 98781, 98782]), + col_indices=tensor([22754, 22754, 106, ..., 4133, 31329, 12170]), + values=tensor([1., 1., 1., ..., 3., 3., 1.]), size=(31379, 31379), + nnz=98782, layout=torch.sparse_csr) +tensor([0.6698, 0.5811, 0.2001, ..., 0.1199, 0.4781, 0.7805]) +Matrix: as-caida_G_078 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98782 +Density: 0.00010032279347811982 +Time: 10.51060438156128 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_079.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_079.json new file mode 100644 index 0000000..f067f53 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_079.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98290, "MATRIX_FILE": "as-caida_G_079", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98392, "MATRIX_DENSITY": 9.992671029032785e-05, "TIME_S": 10.76154351234436, "TIME_S_1KI": 0.1094876743549126, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 768.5910512018203, "W": 73.13, "J_1KI": 7.819626118647068, "W_1KI": 0.7440227897039373, "W_D": 56.72725, "J_D": 596.199325985074, "W_D_1KI": 0.5771416217316105, "J_D_1KI": 0.005871824414809345} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_079.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_079.output new file mode 100644 index 0000000..a560e41 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_079.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 98391, 98391, 98392]), + col_indices=tensor([22754, 106, 329, ..., 4133, 31329, 12170]), + values=tensor([1., 1., 1., ..., 3., 3., 1.]), size=(31379, 31379), + nnz=98392, layout=torch.sparse_csr) +tensor([0.6584, 0.4659, 0.7855, ..., 0.5238, 0.9657, 0.5027]) +Matrix: as-caida_G_079 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98392 +Density: 9.992671029032785e-05 +Time: 10.76154351234436 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_080.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_080.json new file mode 100644 index 0000000..49defd3 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_080.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96581, "MATRIX_FILE": "as-caida_G_080", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98112, "MATRIX_DENSITY": 9.964234287345156e-05, "TIME_S": 10.783490896224976, "TIME_S_1KI": 0.11165230113816357, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 787.5587756109238, "W": 72.67, "J_1KI": 8.154386221005414, "W_1KI": 0.7524254252906887, "W_D": 56.2915, "J_D": 610.0573113706112, "W_D_1KI": 0.5828423810066162, "J_D_1KI": 0.00603475198027165} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_080.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_080.output new file mode 100644 index 0000000..839e6fb --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_080.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98111, 98111, 98112]), + col_indices=tensor([22754, 22754, 106, ..., 4133, 31329, 12170]), + values=tensor([1., 1., 1., ..., 3., 3., 1.]), size=(31379, 31379), + nnz=98112, layout=torch.sparse_csr) +tensor([0.7531, 0.7490, 0.1444, ..., 0.5115, 0.6936, 0.1624]) +Matrix: as-caida_G_080 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98112 +Density: 9.964234287345156e-05 +Time: 10.783490896224976 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_081.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_081.json new file mode 100644 index 0000000..cba9f52 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_081.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98673, "MATRIX_FILE": "as-caida_G_081", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 85988, "MATRIX_DENSITY": 8.732923372270826e-05, "TIME_S": 10.454664468765259, "TIME_S_1KI": 0.1059526361696235, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 767.0234267854692, "W": 73.18, "J_1KI": 7.773387114869003, "W_1KI": 0.7416415838172551, "W_D": 56.834500000000006, "J_D": 595.7009148625136, "W_D_1KI": 0.5759883656116669, "J_D_1KI": 0.005837345227282711} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_081.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_081.output new file mode 100644 index 0000000..4c9c299 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_081.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 85987, 85987, 85988]), + col_indices=tensor([22754, 106, 329, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=85988, layout=torch.sparse_csr) +tensor([0.8443, 0.9944, 0.2211, ..., 0.3999, 0.9498, 0.3629]) +Matrix: as-caida_G_081 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 85988 +Density: 8.732923372270826e-05 +Time: 10.454664468765259 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_082.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_082.json new file mode 100644 index 0000000..ebebf38 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_082.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98891, "MATRIX_FILE": "as-caida_G_082", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98400, "MATRIX_DENSITY": 9.993483507366717e-05, "TIME_S": 10.541533708572388, "TIME_S_1KI": 0.10659750339841227, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 773.0425792884827, "W": 72.98, "J_1KI": 7.817117627372387, "W_1KI": 0.7379842452801569, "W_D": 56.47925000000001, "J_D": 598.257948702097, "W_D_1KI": 0.5711262905623363, "J_D_1KI": 0.005775311105786536} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_082.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_082.output new file mode 100644 index 0000000..d4dd1d9 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_082.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 1, ..., 98399, 98399, 98400]), + col_indices=tensor([22754, 106, 329, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98400, layout=torch.sparse_csr) +tensor([0.5988, 0.9643, 0.6852, ..., 0.1509, 0.4358, 0.6565]) +Matrix: as-caida_G_082 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98400 +Density: 9.993483507366717e-05 +Time: 10.541533708572388 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_083.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_083.json new file mode 100644 index 0000000..616bb18 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_083.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97089, "MATRIX_FILE": "as-caida_G_083", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 98450, "MATRIX_DENSITY": 9.998561496953794e-05, "TIME_S": 10.488253116607666, "TIME_S_1KI": 0.10802720304676808, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 752.1357908248901, "W": 72.36, "J_1KI": 7.746869272779513, "W_1KI": 0.7452955535642555, "W_D": 55.626999999999995, "J_D": 578.206987786293, "W_D_1KI": 0.5729485317595195, "J_D_1KI": 0.0059012713258919085} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_083.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_083.output new file mode 100644 index 0000000..0341e58 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_083.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 1, 2, ..., 98449, 98449, 98450]), + col_indices=tensor([22754, 22754, 106, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=98450, layout=torch.sparse_csr) +tensor([0.4429, 0.9819, 0.6373, ..., 0.3394, 0.3613, 0.0698]) +Matrix: as-caida_G_083 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 98450 +Density: 9.998561496953794e-05 +Time: 10.488253116607666 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_084.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_084.json new file mode 100644 index 0000000..082a4e6 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_084.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96240, "MATRIX_FILE": "as-caida_G_084", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 97972, "MATRIX_DENSITY": 9.950015916501341e-05, "TIME_S": 10.660627365112305, "TIME_S_1KI": 0.11077127353607964, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 773.8550817561149, "W": 72.69, "J_1KI": 8.040888214423472, "W_1KI": 0.7552992518703241, "W_D": 56.26649999999999, "J_D": 599.011101356864, "W_D_1KI": 0.5846477556109726, "J_D_1KI": 0.006074893553729973} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_084.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_084.output new file mode 100644 index 0000000..b6bf5a1 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_084.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 97971, 97971, 97972]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=97972, layout=torch.sparse_csr) +tensor([0.3687, 0.6595, 0.6180, ..., 0.8974, 0.2967, 0.6497]) +Matrix: as-caida_G_084 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 97972 +Density: 9.950015916501341e-05 +Time: 10.660627365112305 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_085.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_085.json new file mode 100644 index 0000000..5fc4358 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_085.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98106, "MATRIX_FILE": "as-caida_G_085", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99166, "MATRIX_DENSITY": 0.0001007127830784073, "TIME_S": 10.558502435684204, "TIME_S_1KI": 0.10762341177587716, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 769.6570807194711, "W": 73.01, "J_1KI": 7.845158101639767, "W_1KI": 0.7441950543289911, "W_D": 56.60575000000001, "J_D": 596.7266990403534, "W_D_1KI": 0.5769856074042363, "J_D_1KI": 0.005881246890141646} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_085.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_085.output new file mode 100644 index 0000000..85975c2 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_085.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99165, 99165, 99166]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99166, layout=torch.sparse_csr) +tensor([0.7290, 0.2845, 0.3684, ..., 0.9543, 0.7218, 0.2767]) +Matrix: as-caida_G_085 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99166 +Density: 0.0001007127830784073 +Time: 10.558502435684204 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_086.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_086.json new file mode 100644 index 0000000..b199e6c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_086.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97459, "MATRIX_FILE": "as-caida_G_086", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99660, "MATRIX_DENSITY": 0.00010121448844961047, "TIME_S": 10.52202296257019, "TIME_S_1KI": 0.10796358430283699, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 757.5080947518348, "W": 72.47, "J_1KI": 7.772582262816516, "W_1KI": 0.7435947424044983, "W_D": 56.04174999999999, "J_D": 585.788316117823, "W_D_1KI": 0.5750289865481893, "J_D_1KI": 0.005900214311127647} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_086.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_086.output new file mode 100644 index 0000000..c9c4dfa --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_086.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99659, 99659, 99660]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99660, layout=torch.sparse_csr) +tensor([0.1622, 0.2225, 0.5645, ..., 0.8188, 0.0337, 0.9900]) +Matrix: as-caida_G_086 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99660 +Density: 0.00010121448844961047 +Time: 10.52202296257019 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_087.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_087.json new file mode 100644 index 0000000..5656176 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_087.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 93546, "MATRIX_FILE": "as-caida_G_087", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99652, "MATRIX_DENSITY": 0.00010120636366627115, "TIME_S": 10.108241319656372, "TIME_S_1KI": 0.10805637140718334, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 721.9213285541534, "W": 72.34, "J_1KI": 7.7172869877296035, "W_1KI": 0.7733093878947256, "W_D": 55.69225, "J_D": 555.7841181942225, "W_D_1KI": 0.5953461398670173, "J_D_1KI": 0.006364207340420941} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_087.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_087.output new file mode 100644 index 0000000..9d28c8f --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_087.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99651, 99651, 99652]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99652, layout=torch.sparse_csr) +tensor([0.1490, 0.6828, 0.8463, ..., 0.6680, 0.3120, 0.5679]) +Matrix: as-caida_G_087 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99652 +Density: 0.00010120636366627115 +Time: 10.108241319656372 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_088.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_088.json new file mode 100644 index 0000000..8db0760 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_088.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98673, "MATRIX_FILE": "as-caida_G_088", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 100366, "MATRIX_DENSITY": 0.00010193150057930568, "TIME_S": 10.546597719192505, "TIME_S_1KI": 0.10688433228129787, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 764.6504058265685, "W": 72.83, "J_1KI": 7.749337770479954, "W_1KI": 0.7380945142034802, "W_D": 56.0405, "J_D": 588.3755467214585, "W_D_1KI": 0.5679415848307034, "J_D_1KI": 0.005755795251291675} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_088.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_088.output new file mode 100644 index 0000000..131e9cc --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_088.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 100365, 100365, + 100366]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=100366, layout=torch.sparse_csr) +tensor([0.4195, 0.2845, 0.8151, ..., 0.6816, 0.4159, 0.9034]) +Matrix: as-caida_G_088 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 100366 +Density: 0.00010193150057930568 +Time: 10.546597719192505 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_089.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_089.json new file mode 100644 index 0000000..ee6e5c7 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_089.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96357, "MATRIX_FILE": "as-caida_G_089", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 101476, "MATRIX_DENSITY": 0.00010305881426763669, "TIME_S": 10.421785593032837, "TIME_S_1KI": 0.10815805383140652, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 753.965559220314, "W": 72.95, "J_1KI": 7.82470976909113, "W_1KI": 0.7570804404454269, "W_D": 56.218500000000006, "J_D": 581.0392431943417, "W_D_1KI": 0.5834397085837044, "J_D_1KI": 0.006054980007510657} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_089.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_089.output new file mode 100644 index 0000000..fa2d5ab --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_089.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 101475, 101475, + 101476]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=101476, layout=torch.sparse_csr) +tensor([0.5440, 0.9877, 0.3766, ..., 0.4626, 0.6471, 0.5053]) +Matrix: as-caida_G_089 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 101476 +Density: 0.00010305881426763669 +Time: 10.421785593032837 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_090.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_090.json new file mode 100644 index 0000000..dab5e5a --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_090.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98279, "MATRIX_FILE": "as-caida_G_090", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 100924, "MATRIX_DENSITY": 0.00010249820421722343, "TIME_S": 10.624969482421875, "TIME_S_1KI": 0.10811027261593907, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 759.7352101063728, "W": 72.87, "J_1KI": 7.7303921499646195, "W_1KI": 0.7414605358214879, "W_D": 56.45875, "J_D": 588.6331864085794, "W_D_1KI": 0.5744742009991962, "J_D_1KI": 0.005845340316844862} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_090.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_090.output new file mode 100644 index 0000000..3d84ada --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_090.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 100923, 100923, + 100924]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 31211, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=100924, layout=torch.sparse_csr) +tensor([0.1602, 0.3930, 0.7970, ..., 0.3050, 0.6728, 0.2557]) +Matrix: as-caida_G_090 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 100924 +Density: 0.00010249820421722343 +Time: 10.624969482421875 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_091.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_091.json new file mode 100644 index 0000000..b5a2718 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_091.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 98775, "MATRIX_FILE": "as-caida_G_091", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 101654, "MATRIX_DENSITY": 0.00010323959069693661, "TIME_S": 10.71744418144226, "TIME_S_1KI": 0.10850361104978244, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 769.3753397750855, "W": 73.12, "J_1KI": 7.78917073930737, "W_1KI": 0.7402682865097444, "W_D": 56.67700000000001, "J_D": 596.3605871503354, "W_D_1KI": 0.5737990382181727, "J_D_1KI": 0.0058091525003105314} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_091.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_091.output new file mode 100644 index 0000000..c29e631 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_091.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 101653, 101653, + 101654]), + col_indices=tensor([ 106, 329, 1040, ..., 19739, 155, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=101654, layout=torch.sparse_csr) +tensor([0.1577, 0.6421, 0.4963, ..., 0.1058, 0.2280, 0.5471]) +Matrix: as-caida_G_091 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 101654 +Density: 0.00010323959069693661 +Time: 10.71744418144226 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_092.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_092.json new file mode 100644 index 0000000..2d9d110 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_092.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96176, "MATRIX_FILE": "as-caida_G_092", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 101762, "MATRIX_DENSITY": 0.00010334927527201746, "TIME_S": 10.418164014816284, "TIME_S_1KI": 0.1083239479164894, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 768.7972375655174, "W": 72.97, "J_1KI": 7.993649533828787, "W_1KI": 0.7587131924804525, "W_D": 56.646499999999996, "J_D": 596.8161260484457, "W_D_1KI": 0.5889878971884877, "J_D_1KI": 0.0061240631466112925} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_092.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_092.output new file mode 100644 index 0000000..d0e0381 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_092.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 101761, 101761, + 101762]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=101762, layout=torch.sparse_csr) +tensor([0.5323, 0.1907, 0.4338, ..., 0.0231, 0.1186, 0.6716]) +Matrix: as-caida_G_092 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 101762 +Density: 0.00010334927527201746 +Time: 10.418164014816284 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_093.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_093.json new file mode 100644 index 0000000..2cb0568 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_093.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97659, "MATRIX_FILE": "as-caida_G_093", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 99916, "MATRIX_DENSITY": 0.0001014744815164688, "TIME_S": 10.485050678253174, "TIME_S_1KI": 0.10736389557801301, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 769.2553848171233, "W": 72.82, "J_1KI": 7.876953325521695, "W_1KI": 0.7456558023326063, "W_D": 56.12049999999999, "J_D": 592.8453285310268, "W_D_1KI": 0.574657737638108, "J_D_1KI": 0.005884329530694642} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_093.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_093.output new file mode 100644 index 0000000..608891b --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_093.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 99914, 99915, 99916]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=99916, layout=torch.sparse_csr) +tensor([0.4705, 0.3767, 0.4814, ..., 0.5201, 0.2367, 0.3139]) +Matrix: as-caida_G_093 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 99916 +Density: 0.0001014744815164688 +Time: 10.485050678253174 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_094.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_094.json new file mode 100644 index 0000000..0e949ae --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_094.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97347, "MATRIX_FILE": "as-caida_G_094", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102476, "MATRIX_DENSITY": 0.000104074412185052, "TIME_S": 10.466264724731445, "TIME_S_1KI": 0.10751502074775234, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 773.97092628479, "W": 73.3, "J_1KI": 7.950639735017925, "W_1KI": 0.75297646563325, "W_D": 56.921, "J_D": 601.0259085273742, "W_D_1KI": 0.5847226930465244, "J_D_1KI": 0.006006581538686599} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_094.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_094.output new file mode 100644 index 0000000..e16723c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_094.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102474, 102475, + 102476]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102476, layout=torch.sparse_csr) +tensor([0.5416, 0.3300, 0.1368, ..., 0.5784, 0.3339, 0.7691]) +Matrix: as-caida_G_094 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102476 +Density: 0.000104074412185052 +Time: 10.466264724731445 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_095.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_095.json new file mode 100644 index 0000000..30201c4 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_095.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97726, "MATRIX_FILE": "as-caida_G_095", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102290, "MATRIX_DENSITY": 0.00010388551097241275, "TIME_S": 10.694494247436523, "TIME_S_1KI": 0.10943345933975118, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 774.3597419738769, "W": 72.82, "J_1KI": 7.923784274132543, "W_1KI": 0.7451445879295171, "W_D": 56.25274999999999, "J_D": 598.1854569530486, "W_D_1KI": 0.5756170312915702, "J_D_1KI": 0.0058901114472256115} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_095.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_095.output new file mode 100644 index 0000000..decb8ae --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_095.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102289, 102289, + 102290]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 25970, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102290, layout=torch.sparse_csr) +tensor([0.8822, 0.2265, 0.4765, ..., 0.5717, 0.6067, 0.9103]) +Matrix: as-caida_G_095 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102290 +Density: 0.00010388551097241275 +Time: 10.694494247436523 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_096.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_096.json new file mode 100644 index 0000000..8cac430 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_096.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95779, "MATRIX_FILE": "as-caida_G_096", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102356, "MATRIX_DENSITY": 0.00010395254043496216, "TIME_S": 10.363560438156128, "TIME_S_1KI": 0.1082028465337509, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 754.4578800201417, "W": 72.9, "J_1KI": 7.877069921591807, "W_1KI": 0.7611271781914617, "W_D": 56.351000000000006, "J_D": 583.1886968040467, "W_D_1KI": 0.5883440002505769, "J_D_1KI": 0.006142724399404638} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_096.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_096.output new file mode 100644 index 0000000..ae51e4b --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_096.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102354, 102355, + 102356]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102356, layout=torch.sparse_csr) +tensor([0.9695, 0.1146, 0.6972, ..., 0.7217, 0.8738, 0.3973]) +Matrix: as-caida_G_096 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102356 +Density: 0.00010395254043496216 +Time: 10.363560438156128 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_097.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_097.json new file mode 100644 index 0000000..24a3b9b --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_097.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97460, "MATRIX_FILE": "as-caida_G_097", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102212, "MATRIX_DENSITY": 0.00010380629433485436, "TIME_S": 10.98289942741394, "TIME_S_1KI": 0.11269135468308988, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 764.4614424037933, "W": 72.44, "J_1KI": 7.843848167492236, "W_1KI": 0.7432792940693618, "W_D": 55.7795, "J_D": 588.64269777143, "W_D_1KI": 0.5723322388672276, "J_D_1KI": 0.005872483468779269} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_097.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_097.output new file mode 100644 index 0000000..5bdb9c2 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_097.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102210, 102211, + 102212]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102212, layout=torch.sparse_csr) +tensor([0.5574, 0.1737, 0.0334, ..., 0.2319, 0.2177, 0.4678]) +Matrix: as-caida_G_097 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102212 +Density: 0.00010380629433485436 +Time: 10.98289942741394 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_098.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_098.json new file mode 100644 index 0000000..bc3805b --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_098.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97771, "MATRIX_FILE": "as-caida_G_098", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102468, "MATRIX_DENSITY": 0.00010406628740171267, "TIME_S": 10.549879789352417, "TIME_S_1KI": 0.10790397755318465, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 768.7171660137177, "W": 72.98, "J_1KI": 7.862425115972198, "W_1KI": 0.7464381053686676, "W_D": 56.5435, "J_D": 595.5872715332508, "W_D_1KI": 0.5783258839533195, "J_D_1KI": 0.005915106564864014} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_098.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_098.output new file mode 100644 index 0000000..89a0872 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_098.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102466, 102467, + 102468]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102468, layout=torch.sparse_csr) +tensor([0.3812, 0.6721, 0.3320, ..., 0.6613, 0.9122, 0.8257]) +Matrix: as-caida_G_098 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102468 +Density: 0.00010406628740171267 +Time: 10.549879789352417 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_099.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_099.json new file mode 100644 index 0000000..0f2968f --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_099.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96955, "MATRIX_FILE": "as-caida_G_099", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 103510, "MATRIX_DENSITY": 0.00010512454043165944, "TIME_S": 10.463958263397217, "TIME_S_1KI": 0.10792592711461212, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 771.0620793437957, "W": 72.67, "J_1KI": 7.952783036911926, "W_1KI": 0.7495229745758342, "W_D": 56.25425, "J_D": 596.8834316351414, "W_D_1KI": 0.580209891186633, "J_D_1KI": 0.0059843215015897375} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_099.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_099.output new file mode 100644 index 0000000..5e9b7b0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_099.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 103508, 103509, + 103510]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=103510, layout=torch.sparse_csr) +tensor([0.6608, 0.2081, 0.0159, ..., 0.0668, 0.2494, 0.7541]) +Matrix: as-caida_G_099 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 103510 +Density: 0.00010512454043165944 +Time: 10.463958263397217 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_100.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_100.json new file mode 100644 index 0000000..0dca978 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_100.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96912, "MATRIX_FILE": "as-caida_G_100", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 102888, "MATRIX_DENSITY": 0.00010449283852702711, "TIME_S": 10.475964784622192, "TIME_S_1KI": 0.10809770497587701, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 752.1479917907715, "W": 72.64, "J_1KI": 7.76114404604973, "W_1KI": 0.7495459798580155, "W_D": 56.28925, "J_D": 582.8448010312319, "W_D_1KI": 0.5808284835727259, "J_D_1KI": 0.005993359785916356} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_100.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_100.output new file mode 100644 index 0000000..a5108e6 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_100.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 102886, 102887, + 102888]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 5128, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=102888, layout=torch.sparse_csr) +tensor([0.0357, 0.4826, 0.6631, ..., 0.7302, 0.3954, 0.7914]) +Matrix: as-caida_G_100 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 102888 +Density: 0.00010449283852702711 +Time: 10.475964784622192 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_101.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_101.json new file mode 100644 index 0000000..3c7a777 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_101.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96489, "MATRIX_FILE": "as-caida_G_101", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 103020, "MATRIX_DENSITY": 0.00010462689745212593, "TIME_S": 10.369633197784424, "TIME_S_1KI": 0.10746958925664504, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 745.5306213521957, "W": 72.58, "J_1KI": 7.726586671560444, "W_1KI": 0.7522100964876826, "W_D": 56.001999999999995, "J_D": 575.2439495310783, "W_D_1KI": 0.5803977655484045, "J_D_1KI": 0.0060151702841609355} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_101.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_101.output new file mode 100644 index 0000000..754de1c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_101.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 103017, 103018, + 103020]), + col_indices=tensor([ 106, 329, 1040, ..., 5128, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=103020, layout=torch.sparse_csr) +tensor([0.3034, 0.5065, 0.0243, ..., 0.4593, 0.1463, 0.7889]) +Matrix: as-caida_G_101 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 103020 +Density: 0.00010462689745212593 +Time: 10.369633197784424 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_102.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_102.json new file mode 100644 index 0000000..e8bf099 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_102.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97432, "MATRIX_FILE": "as-caida_G_102", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104096, "MATRIX_DENSITY": 0.00010571968081126482, "TIME_S": 10.462616682052612, "TIME_S_1KI": 0.1073837823513077, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 763.0509541869164, "W": 72.43, "J_1KI": 7.831625689577515, "W_1KI": 0.7433902619262666, "W_D": 56.029250000000005, "J_D": 590.2688481965662, "W_D_1KI": 0.5750600418753593, "J_D_1KI": 0.005902168095444611} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_102.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_102.output new file mode 100644 index 0000000..29be31f --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_102.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104094, 104094, + 104096]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104096, layout=torch.sparse_csr) +tensor([0.1300, 0.8580, 0.0102, ..., 0.1227, 0.2756, 0.8761]) +Matrix: as-caida_G_102 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104096 +Density: 0.00010571968081126482 +Time: 10.462616682052612 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_103.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_103.json new file mode 100644 index 0000000..56be8a4 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_103.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 94305, "MATRIX_FILE": "as-caida_G_103", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104634, "MATRIX_DENSITY": 0.00010626607249083426, "TIME_S": 10.381156206130981, "TIME_S_1KI": 0.1100806553855149, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 746.2515045118332, "W": 72.51, "J_1KI": 7.913170081245249, "W_1KI": 0.7688881819627804, "W_D": 56.154250000000005, "J_D": 577.9229561058283, "W_D_1KI": 0.5954535814643975, "J_D_1KI": 0.006314125247488442} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_103.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_103.output new file mode 100644 index 0000000..a398f1e --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_103.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104632, 104632, + 104634]), + col_indices=tensor([ 106, 329, 1040, ..., 25970, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104634, layout=torch.sparse_csr) +tensor([0.1194, 0.0978, 0.1847, ..., 0.2504, 0.3058, 0.7776]) +Matrix: as-caida_G_103 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104634 +Density: 0.00010626607249083426 +Time: 10.381156206130981 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_104.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_104.json new file mode 100644 index 0000000..6c11f94 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_104.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97560, "MATRIX_FILE": "as-caida_G_104", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104824, "MATRIX_DENSITY": 0.00010645903609514317, "TIME_S": 10.544718027114868, "TIME_S_1KI": 0.10808444062233363, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 765.9797556567192, "W": 72.81, "J_1KI": 7.851371009191465, "W_1KI": 0.7463099630996309, "W_D": 56.482, "J_D": 594.2050344595909, "W_D_1KI": 0.5789462894628946, "J_D_1KI": 0.005934258809582766} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_104.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_104.output new file mode 100644 index 0000000..ca1c535 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_104.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104823, 104823, + 104824]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104824, layout=torch.sparse_csr) +tensor([0.0903, 0.0409, 0.5175, ..., 0.2375, 0.7454, 0.0942]) +Matrix: as-caida_G_104 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104824 +Density: 0.00010645903609514317 +Time: 10.544718027114868 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_105.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_105.json new file mode 100644 index 0000000..26c8185 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_105.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96381, "MATRIX_FILE": "as-caida_G_105", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104726, "MATRIX_DENSITY": 0.00010635950749923647, "TIME_S": 10.497961282730103, "TIME_S_1KI": 0.10892148123312793, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 769.2273417806625, "W": 72.74, "J_1KI": 7.981109780772792, "W_1KI": 0.7547130658532283, "W_D": 56.09025, "J_D": 593.1558139581084, "W_D_1KI": 0.5819637687926044, "J_D_1KI": 0.006038158649449626} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_105.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_105.output new file mode 100644 index 0000000..62dc64c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_105.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104725, 104725, + 104726]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104726, layout=torch.sparse_csr) +tensor([0.0576, 0.3484, 0.1476, ..., 0.0685, 0.4081, 0.8597]) +Matrix: as-caida_G_105 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104726 +Density: 0.00010635950749923647 +Time: 10.497961282730103 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_106.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_106.json new file mode 100644 index 0000000..f55812a --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_106.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96767, "MATRIX_FILE": "as-caida_G_106", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105092, "MATRIX_DENSITY": 0.00010673121633701047, "TIME_S": 10.491316080093384, "TIME_S_1KI": 0.1084183252564757, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 774.7813075876236, "W": 73.34, "J_1KI": 8.00666867411022, "W_1KI": 0.7579030041233065, "W_D": 56.85125000000001, "J_D": 600.5902074310185, "W_D_1KI": 0.5875065879897072, "J_D_1KI": 0.006071352713111983} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_106.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_106.output new file mode 100644 index 0000000..e861547 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_106.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105091, 105091, + 105092]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105092, layout=torch.sparse_csr) +tensor([0.1804, 0.5643, 0.7723, ..., 0.2556, 0.2764, 0.6258]) +Matrix: as-caida_G_106 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105092 +Density: 0.00010673121633701047 +Time: 10.491316080093384 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_107.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_107.json new file mode 100644 index 0000000..94a367f --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_107.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 97907, "MATRIX_FILE": "as-caida_G_107", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105332, "MATRIX_DENSITY": 0.00010697495983719015, "TIME_S": 10.767481327056885, "TIME_S_1KI": 0.10997662401112163, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 781.3813791799545, "W": 72.71, "J_1KI": 7.9808530460534435, "W_1KI": 0.7426435290632947, "W_D": 55.841499999999996, "J_D": 600.1032634503841, "W_D_1KI": 0.5703524773509554, "J_D_1KI": 0.005825451472836012} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_107.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_107.output new file mode 100644 index 0000000..c49c584 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_107.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105330, 105330, + 105332]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105332, layout=torch.sparse_csr) +tensor([0.6274, 0.2404, 0.9149, ..., 0.2359, 0.6309, 0.5106]) +Matrix: as-caida_G_107 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105332 +Density: 0.00010697495983719015 +Time: 10.767481327056885 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_108.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_108.json new file mode 100644 index 0000000..fcd111d --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_108.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96697, "MATRIX_FILE": "as-caida_G_108", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105524, "MATRIX_DENSITY": 0.0001071699546373339, "TIME_S": 10.530481815338135, "TIME_S_1KI": 0.10890184613109129, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 756.1363549733162, "W": 72.59, "J_1KI": 7.819646472727347, "W_1KI": 0.7506954714210369, "W_D": 56.18325, "J_D": 585.2348514334559, "W_D_1KI": 0.5810237132486014, "J_D_1KI": 0.006008704646975618} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_108.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_108.output new file mode 100644 index 0000000..4375377 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_108.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105522, 105522, + 105524]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105524, layout=torch.sparse_csr) +tensor([0.6995, 0.0162, 0.7222, ..., 0.8605, 0.1583, 0.9236]) +Matrix: as-caida_G_108 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105524 +Density: 0.0001071699546373339 +Time: 10.530481815338135 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_109.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_109.json new file mode 100644 index 0000000..24863b0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_109.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96087, "MATRIX_FILE": "as-caida_G_109", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104802, "MATRIX_DENSITY": 0.00010643669294096003, "TIME_S": 10.567811012268066, "TIME_S_1KI": 0.10998169380111844, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 761.5258847475052, "W": 72.55, "J_1KI": 7.925378924802577, "W_1KI": 0.7550449072194989, "W_D": 56.176249999999996, "J_D": 589.6577323645353, "W_D_1KI": 0.5846394413396192, "J_D_1KI": 0.00608448012051182} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_109.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_109.output new file mode 100644 index 0000000..472ab90 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_109.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104801, 104801, + 104802]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104802, layout=torch.sparse_csr) +tensor([0.7801, 0.9880, 0.3738, ..., 0.0953, 0.8465, 0.5989]) +Matrix: as-caida_G_109 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104802 +Density: 0.00010643669294096003 +Time: 10.567811012268066 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_110.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_110.json new file mode 100644 index 0000000..24d5fd1 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_110.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95654, "MATRIX_FILE": "as-caida_G_110", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104846, "MATRIX_DENSITY": 0.0001064813792493263, "TIME_S": 10.277755975723267, "TIME_S_1KI": 0.10744721575389704, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 763.9345809650421, "W": 72.74, "J_1KI": 7.986436332668179, "W_1KI": 0.760449118698643, "W_D": 56.107749999999996, "J_D": 589.2583239639997, "W_D_1KI": 0.5865698245760762, "J_D_1KI": 0.006132203823949613} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_110.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_110.output new file mode 100644 index 0000000..fa40e03 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_110.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104844, 104844, + 104846]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104846, layout=torch.sparse_csr) +tensor([0.4577, 0.7409, 0.8785, ..., 0.7451, 0.1329, 0.5541]) +Matrix: as-caida_G_110 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104846 +Density: 0.0001064813792493263 +Time: 10.277755975723267 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_111.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_111.json new file mode 100644 index 0000000..9767454 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_111.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 94842, "MATRIX_FILE": "as-caida_G_111", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104766, "MATRIX_DENSITY": 0.00010640013141593308, "TIME_S": 10.353078365325928, "TIME_S_1KI": 0.10916132478570599, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 750.004163017273, "W": 73.12, "J_1KI": 7.907932804214092, "W_1KI": 0.770966449463318, "W_D": 56.679, "J_D": 581.3660551922321, "W_D_1KI": 0.5976149807047512, "J_D_1KI": 0.006301163837801303} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_111.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_111.output new file mode 100644 index 0000000..3d6e5ca --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_111.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104764, 104764, + 104766]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104766, layout=torch.sparse_csr) +tensor([0.2701, 0.9785, 0.0234, ..., 0.3539, 0.2474, 0.0280]) +Matrix: as-caida_G_111 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104766 +Density: 0.00010640013141593308 +Time: 10.353078365325928 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_112.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_112.json new file mode 100644 index 0000000..ae41b43 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_112.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95719, "MATRIX_FILE": "as-caida_G_112", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 104730, "MATRIX_DENSITY": 0.00010636356989090612, "TIME_S": 11.165848016738892, "TIME_S_1KI": 0.1166523680433236, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 762.7021032619476, "W": 72.38, "J_1KI": 7.968136976587173, "W_1KI": 0.7561717109455802, "W_D": 56.00225, "J_D": 590.1220483890771, "W_D_1KI": 0.5850693174813778, "J_D_1KI": 0.00611236345429202} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_112.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_112.output new file mode 100644 index 0000000..abe6fce --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_112.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 104728, 104728, + 104730]), + col_indices=tensor([ 106, 329, 1040, ..., 882, 2616, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=104730, layout=torch.sparse_csr) +tensor([0.2586, 0.6830, 0.5062, ..., 0.6449, 0.3619, 0.0955]) +Matrix: as-caida_G_112 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 104730 +Density: 0.00010636356989090612 +Time: 11.165848016738892 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_113.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_113.json new file mode 100644 index 0000000..18e3908 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_113.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95628, "MATRIX_FILE": "as-caida_G_113", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105382, "MATRIX_DENSITY": 0.00010702573973306091, "TIME_S": 10.311292171478271, "TIME_S_1KI": 0.10782712355668081, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 754.0979419112206, "W": 72.37, "J_1KI": 7.885744153503373, "W_1KI": 0.7567867151880203, "W_D": 55.7135, "J_D": 580.5366268712282, "W_D_1KI": 0.5826065587484838, "J_D_1KI": 0.006092426472879112} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_113.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_113.output new file mode 100644 index 0000000..f2c4060 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_113.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105381, 105381, + 105382]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105382, layout=torch.sparse_csr) +tensor([0.3171, 0.5022, 0.6419, ..., 0.3495, 0.4203, 0.0084]) +Matrix: as-caida_G_113 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105382 +Density: 0.00010702573973306091 +Time: 10.311292171478271 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_114.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_114.json new file mode 100644 index 0000000..58f3ff3 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_114.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 183180, "MATRIX_FILE": "as-caida_G_114", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 36406, "MATRIX_DENSITY": 3.6973857781422023e-05, "TIME_S": 10.442456483840942, "TIME_S_1KI": 0.05700653173840453, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 802.448795800209, "W": 75.06, "J_1KI": 4.380657254068179, "W_1KI": 0.4097608909269571, "W_D": 58.30275, "J_D": 623.3009796075225, "W_D_1KI": 0.318281198820832, "J_D_1KI": 0.001737532475274768} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_114.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_114.output new file mode 100644 index 0000000..67103ca --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_114.output @@ -0,0 +1,14 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 36405, 36405, 36406]), + col_indices=tensor([ 106, 329, 1040, ..., 1683, 1683, 12170]), + values=tensor([1., 1., 1., ..., 2., 2., 1.]), size=(31379, 31379), + nnz=36406, layout=torch.sparse_csr) +tensor([0.6281, 0.2503, 0.5583, ..., 0.1272, 0.1060, 0.0582]) +Matrix: as-caida_G_114 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 36406 +Density: 3.6973857781422023e-05 +Time: 10.442456483840942 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_115.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_115.json new file mode 100644 index 0000000..9da34e0 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_115.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96720, "MATRIX_FILE": "as-caida_G_115", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106312, "MATRIX_DENSITY": 0.00010797024579625715, "TIME_S": 10.5066397190094, "TIME_S_1KI": 0.10862944291779776, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 767.1454833984375, "W": 72.46, "J_1KI": 7.931611697667882, "W_1KI": 0.749172870140612, "W_D": 56.01299999999999, "J_D": 593.0184924316405, "W_D_1KI": 0.5791253101736972, "J_D_1KI": 0.0059876479546494745} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_115.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_115.output new file mode 100644 index 0000000..038ed82 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_115.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106311, 106311, + 106312]), + col_indices=tensor([ 106, 329, 1040, ..., 160, 882, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106312, layout=torch.sparse_csr) +tensor([0.7497, 0.5736, 0.1641, ..., 0.9132, 0.5950, 0.0994]) +Matrix: as-caida_G_115 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106312 +Density: 0.00010797024579625715 +Time: 10.5066397190094 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_116.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_116.json new file mode 100644 index 0000000..d6f930d --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_116.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 95418, "MATRIX_FILE": "as-caida_G_116", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106578, "MATRIX_DENSITY": 0.00010824039484228964, "TIME_S": 10.570079326629639, "TIME_S_1KI": 0.11077657597758954, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 760.4319326210023, "W": 72.56, "J_1KI": 7.96948094301916, "W_1KI": 0.7604435221865895, "W_D": 56.04225, "J_D": 587.3251995028854, "W_D_1KI": 0.5873341507891593, "J_D_1KI": 0.006155381068447875} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_116.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_116.output new file mode 100644 index 0000000..6ee728c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_116.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106577, 106577, + 106578]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106578, layout=torch.sparse_csr) +tensor([0.1021, 0.5699, 0.6317, ..., 0.6853, 0.8698, 0.7092]) +Matrix: as-caida_G_116 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106578 +Density: 0.00010824039484228964 +Time: 10.570079326629639 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_117.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_117.json new file mode 100644 index 0000000..d411b40 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_117.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 93726, "MATRIX_FILE": "as-caida_G_117", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106348, "MATRIX_DENSITY": 0.0001080068073212841, "TIME_S": 10.230540752410889, "TIME_S_1KI": 0.10915371137582837, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 739.2993455982208, "W": 72.52, "J_1KI": 7.887878983400773, "W_1KI": 0.773744745321469, "W_D": 56.3315, "J_D": 574.2669758213758, "W_D_1KI": 0.6010231952713228, "J_D_1KI": 0.00641255569715258} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_117.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_117.output new file mode 100644 index 0000000..356f986 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_117.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106347, 106347, + 106348]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106348, layout=torch.sparse_csr) +tensor([0.8268, 0.4882, 0.7553, ..., 0.6356, 0.2888, 0.8016]) +Matrix: as-caida_G_117 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106348 +Density: 0.0001080068073212841 +Time: 10.230540752410889 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_118.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_118.json new file mode 100644 index 0000000..8fb7cde --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_118.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 94355, "MATRIX_FILE": "as-caida_G_118", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 107202, "MATRIX_DENSITY": 0.00010887412794275679, "TIME_S": 11.346534013748169, "TIME_S_1KI": 0.12025365919928112, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 783.2714931821823, "W": 72.58, "J_1KI": 8.301324711803108, "W_1KI": 0.7692226167134757, "W_D": 56.10225, "J_D": 605.4463092915415, "W_D_1KI": 0.5945869323300301, "J_D_1KI": 0.006301594322823699} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_118.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_118.output new file mode 100644 index 0000000..2be4a87 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_118.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 107201, 107201, + 107202]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=107202, layout=torch.sparse_csr) +tensor([0.5219, 0.0130, 0.8236, ..., 0.5517, 0.5741, 0.8242]) +Matrix: as-caida_G_118 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 107202 +Density: 0.00010887412794275679 +Time: 11.346534013748169 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_119.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_119.json new file mode 100644 index 0000000..9a7d50e --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_119.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 93160, "MATRIX_FILE": "as-caida_G_119", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106462, "MATRIX_DENSITY": 0.00010812258548386945, "TIME_S": 10.205135107040405, "TIME_S_1KI": 0.10954417246715764, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 768.6024159955978, "W": 72.77, "J_1KI": 8.250347960450812, "W_1KI": 0.7811292400171748, "W_D": 56.37199999999999, "J_D": 595.4054609661101, "W_D_1KI": 0.6051094890510949, "J_D_1KI": 0.00649537880046259} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_119.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_119.output new file mode 100644 index 0000000..483709d --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_119.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106461, 106461, + 106462]), + col_indices=tensor([ 106, 329, 1040, ..., 31344, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106462, layout=torch.sparse_csr) +tensor([0.4206, 0.7321, 0.4924, ..., 0.6054, 0.2846, 0.8263]) +Matrix: as-caida_G_119 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106462 +Density: 0.00010812258548386945 +Time: 10.205135107040405 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_120.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_120.json new file mode 100644 index 0000000..c05d35c --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_120.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 96712, "MATRIX_FILE": "as-caida_G_120", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106510, "MATRIX_DENSITY": 0.0001081713341839054, "TIME_S": 10.57369327545166, "TIME_S_1KI": 0.10933176105810716, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 781.6079609036445, "W": 72.55, "J_1KI": 8.081809505579914, "W_1KI": 0.7501654396558854, "W_D": 56.268, "J_D": 606.1959578790664, "W_D_1KI": 0.5818099098353876, "J_D_1KI": 0.006015901954621842} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_120.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_120.output new file mode 100644 index 0000000..a27f3fb --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_120.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106509, 106509, + 106510]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106510, layout=torch.sparse_csr) +tensor([0.2676, 0.4597, 0.3080, ..., 0.8188, 0.9703, 0.7361]) +Matrix: as-caida_G_120 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106510 +Density: 0.0001081713341839054 +Time: 10.57369327545166 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_121.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_121.json new file mode 100644 index 0000000..938cf8f --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_121.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 92073, "MATRIX_FILE": "as-caida_G_121", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 106762, "MATRIX_DENSITY": 0.00010842726485909405, "TIME_S": 10.215637445449829, "TIME_S_1KI": 0.11095149984740184, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 737.4823203468322, "W": 72.08, "J_1KI": 8.009756609938117, "W_1KI": 0.7828570807945869, "W_D": 55.525, "J_D": 568.1008024036884, "W_D_1KI": 0.6030540983784606, "J_D_1KI": 0.006549738776606178} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_121.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_121.output new file mode 100644 index 0000000..f579498 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_121.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 106761, 106761, + 106762]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=106762, layout=torch.sparse_csr) +tensor([0.9980, 0.3488, 0.0245, ..., 0.7837, 0.5177, 0.0811]) +Matrix: as-caida_G_121 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 106762 +Density: 0.00010842726485909405 +Time: 10.215637445449829 seconds + diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_122.json b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_122.json new file mode 100644 index 0000000..c01d6b3 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_122.json @@ -0,0 +1 @@ +{"CPU": "XEON_4216", "ITERATIONS": 91535, "MATRIX_FILE": "as-caida_G_122", "MATRIX_SHAPE": [31379, 31379], "MATRIX_SIZE": 984641641, "MATRIX_NNZ": 105722, "MATRIX_DENSITY": 0.00010737104302498212, "TIME_S": 10.055411577224731, "TIME_S_1KI": 0.10985318814906572, "BASELINE_TIME_S": 10, "BASELINE_DELAY_S": 10, "J": 725.4239826345444, "W": 72.11, "J_1KI": 7.925099498929855, "W_1KI": 0.7877860927514065, "W_D": 55.7695, "J_D": 561.0391457431316, "W_D_1KI": 0.6092696782651446, "J_D_1KI": 0.006656138944285186} diff --git a/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_122.output b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_122.output new file mode 100644 index 0000000..4deeaa4 --- /dev/null +++ b/pytorch/output_as-caida/xeon_4216_10_10_10_as-caida_G_122.output @@ -0,0 +1,15 @@ +/nfshomes/vut/ampere_research/pytorch/spmv.py:47: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ../aten/src/ATen/SparseCsrTensorImpl.cpp:53.) + matrix = matrix.to_sparse_csr().type(torch.float32) +tensor(crow_indices=tensor([ 0, 0, 0, ..., 105721, 105721, + 105722]), + col_indices=tensor([ 106, 329, 1040, ..., 155, 160, 12170]), + values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(31379, 31379), + nnz=105722, layout=torch.sparse_csr) +tensor([0.3848, 0.8643, 0.9071, ..., 0.4483, 0.4189, 0.0606]) +Matrix: as-caida_G_122 +Shape: torch.Size([31379, 31379]) +Size: 984641641 +NNZ: 105722 +Density: 0.00010737104302498212 +Time: 10.055411577224731 seconds +