srun: Job time limit was unset; set to partition default of 60 minutes srun: ################################################################################ srun: # Please note that the oasis compute nodes have aarch64 architecture CPUs. # srun: # All submission nodes and all other compute nodes have x86_64 architecture # srun: # CPUs. Programs, environments, or other software that was built on x86_64 # srun: # nodes may need to be rebuilt to properly execute on these nodes. # srun: ################################################################################ srun: job 3394141 queued and waiting for resources srun: job 3394141 has been allocated resources /nfshomes/vut/ampere_research/pytorch/spmv.py:20: UserWarning: Sparse CSR tensor support is in beta state. If 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.) ).to_sparse_csr().type(torch.float) tensor(crow_indices=tensor([ 0, 9, 9, ..., 65369, 65369, 65369]), col_indices=tensor([ 1, 2, 3, ..., 15065, 9401, 26517]), values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(26518, 26518), nnz=65369, layout=torch.sparse_csr) tensor([0.6616, 0.1149, 0.0110, ..., 0.2481, 0.7877, 0.5589]) Shape: torch.Size([26518, 26518]) NNZ: 65369 Density: 9.295875717624285e-05 Time: 0.16974925994873047 seconds Performance counter stats for 'apptainer run pytorch-altra.sif -c numactl --cpunodebind=0 --membind=0 python spmv.py matrices/p2p-Gnutella24.mtx 100': 61.92 msec task-clock:u # 0.017 CPUs utilized 0 context-switches:u # 0.000 /sec 0 cpu-migrations:u # 0.000 /sec 3,281 page-faults:u # 52.988 K/sec 66,250,810 cycles:u # 1.070 GHz (62.94%) 75,178,179 instructions:u # 1.13 insn per cycle (83.47%) branches:u 367,749 branch-misses:u 33,064,095 L1-dcache-loads:u # 533.986 M/sec 465,542 L1-dcache-load-misses:u # 1.41% of all L1-dcache accesses LLC-loads:u LLC-load-misses:u 31,552,264 L1-icache-loads:u # 509.570 M/sec 296,060 L1-icache-load-misses:u # 0.94% of all L1-icache accesses 73,155,896 dTLB-loads:u # 1.181 G/sec (17.31%) dTLB-load-misses:u (0.00%) iTLB-loads:u (0.00%) iTLB-load-misses:u (0.00%) 3.675971385 seconds time elapsed 14.857293000 seconds user 29.791187000 seconds sys /nfshomes/vut/ampere_research/pytorch/spmv.py:20: UserWarning: Sparse CSR tensor support is in beta state. If 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.) ).to_sparse_csr().type(torch.float) tensor(crow_indices=tensor([ 0, 9, 9, ..., 65369, 65369, 65369]), col_indices=tensor([ 1, 2, 3, ..., 15065, 9401, 26517]), values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(26518, 26518), nnz=65369, layout=torch.sparse_csr) tensor([0.1683, 0.8999, 0.0578, ..., 0.5893, 0.0628, 0.8262]) Shape: torch.Size([26518, 26518]) NNZ: 65369 Density: 9.295875717624285e-05 Time: 0.2227163314819336 seconds Performance counter stats for 'apptainer run pytorch-altra.sif -c numactl --cpunodebind=0 --membind=0 python spmv.py matrices/p2p-Gnutella24.mtx 100': 332,366 BR_MIS_PRED_RETIRED:u # 0.0 per branch branch_misprediction_ratio 19,076,182 BR_RETIRED:u 3.532329673 seconds time elapsed 14.883993000 seconds user 28.516661000 seconds sys /nfshomes/vut/ampere_research/pytorch/spmv.py:20: UserWarning: Sparse CSR tensor support is in beta state. If 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.) ).to_sparse_csr().type(torch.float) tensor(crow_indices=tensor([ 0, 9, 9, ..., 65369, 65369, 65369]), col_indices=tensor([ 1, 2, 3, ..., 15065, 9401, 26517]), values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(26518, 26518), nnz=65369, layout=torch.sparse_csr) tensor([0.8389, 0.5614, 0.9033, ..., 0.2231, 0.0349, 0.5167]) Shape: torch.Size([26518, 26518]) NNZ: 65369 Density: 9.295875717624285e-05 Time: 0.17095375061035156 seconds Performance counter stats for 'apptainer run pytorch-altra.sif -c numactl --cpunodebind=0 --membind=0 python spmv.py matrices/p2p-Gnutella24.mtx 100': 27,005,133 L1I_TLB:u # 0.0 per TLB access itlb_walk_ratio 4,791 ITLB_WALK:u 13,403 DTLB_WALK:u # 0.0 per TLB access dtlb_walk_ratio 36,457,054 L1D_TLB:u 3.579041343 seconds time elapsed 14.885159000 seconds user 29.562650000 seconds sys /nfshomes/vut/ampere_research/pytorch/spmv.py:20: UserWarning: Sparse CSR tensor support is in beta state. If 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.) ).to_sparse_csr().type(torch.float) tensor(crow_indices=tensor([ 0, 9, 9, ..., 65369, 65369, 65369]), col_indices=tensor([ 1, 2, 3, ..., 15065, 9401, 26517]), values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(26518, 26518), nnz=65369, layout=torch.sparse_csr) tensor([0.8849, 0.5982, 0.0578, ..., 0.9975, 0.2204, 0.0718]) Shape: torch.Size([26518, 26518]) NNZ: 65369 Density: 9.295875717624285e-05 Time: 0.18003463745117188 seconds Performance counter stats for 'apptainer run pytorch-altra.sif -c numactl --cpunodebind=0 --membind=0 python spmv.py matrices/p2p-Gnutella24.mtx 100': 32,367,686 L1I_CACHE:u # 0.0 per cache access l1i_cache_miss_ratio 287,524 L1I_CACHE_REFILL:u 467,557 L1D_CACHE_REFILL:u # 0.0 per cache access l1d_cache_miss_ratio 34,022,862 L1D_CACHE:u 3.405321132 seconds time elapsed 15.291636000 seconds user 28.005015000 seconds sys /nfshomes/vut/ampere_research/pytorch/spmv.py:20: UserWarning: Sparse CSR tensor support is in beta state. If 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.) ).to_sparse_csr().type(torch.float) tensor(crow_indices=tensor([ 0, 9, 9, ..., 65369, 65369, 65369]), col_indices=tensor([ 1, 2, 3, ..., 15065, 9401, 26517]), values=tensor([1., 1., 1., ..., 1., 1., 1.]), size=(26518, 26518), nnz=65369, layout=torch.sparse_csr) tensor([0.2790, 0.1291, 0.6053, ..., 0.1651, 0.4973, 0.6821]) Shape: torch.Size([26518, 26518]) NNZ: 65369 Density: 9.295875717624285e-05 Time: 0.22036528587341309 seconds Performance counter stats for 'apptainer run pytorch-altra.sif -c numactl --cpunodebind=0 --membind=0 python spmv.py matrices/p2p-Gnutella24.mtx 100': 535,707 LL_CACHE_MISS_RD:u # 1.0 per cache access ll_cache_read_miss_ratio 556,316 LL_CACHE_RD:u 150,149 L2D_TLB:u # 0.1 per TLB access l2_tlb_miss_ratio 18,418 L2D_TLB_REFILL:u 297,042 L2D_CACHE_REFILL:u # 0.2 per cache access l2_cache_miss_ratio 1,687,364 L2D_CACHE:u 3.505209576 seconds time elapsed 15.297738000 seconds user 29.848441000 seconds sys