- 21 Apr, 2026 4 commits
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* Update gpu-hpcg metrics to encode process and problem shape * Fix tests
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- Add BW150 config - Update BW1000 config - Merge summary rules
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- Add `numactl` support for local runner modes, including `cpunodebind`, `membind`, and `physcpubind`. - Add `gpu_affinity` resolution through `sb node topo --get gpu-numa-affinity --gpu-id`. - Add `sb node topo` support for GPU NUMA topology queries. - Update BW1000 config to use the new local `numactl` semantics. - Document the new `numactl` mode fields and limitations.
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- 20 Apr, 2026 3 commits
- 18 Apr, 2026 11 commits
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* Fix some lint warnings * Exclude some paths in cpplint * Fix some tests and formatting
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Adds opt-in deterministic training mode to SuperBench's PyTorch model benchmarks. When enabled --enable-determinism. PyTorch deterministic algorithms are enforced, and per-step numerical fingerprints (loss, activation means) are recorded as metrics. These can be compared across runs using the existing sb result diagnosis pipeline to verify bit-exact reproducibility — useful for hardware validation and platform comparison. Flags added - --enable-determinism --check-frequency: Number of steps after which you want the metrics to be recorded --deterministic-seed Changes - Updated pytorch_base.py to handle deterministic settings, logging. Added a new example script: pytorch_deterministic_example.py Added a test file: test_pytorch_determinism_all.py to verify everything works as expected. Usage - Step 1: Run 1 - Run with --enable-determinism and the necessary metrics will be recorded in the results-summary.jsonl file Step 2: Generate the baseline file from the Run 1 results using - sb result generate-baseline Step 3: Run 2 - Run with --enable-determinism and the necessary metrics will be recorded in the results-summary.jsonl file on a different machine (or the same machine) Step 4: Run diagnosis on the results generated from the 2 runs using the - sb result diagnosis command Note - 1. Make sure all the parameters are constant between the 2 runs 2. Running the diagnosis command requires the rules.yaml file --------- Co-authored-by:
Aishwarya Tonpe <aishwarya.tonpe25@gmail.com> Co-authored-by:
Ubuntu <rdadmin@HPCPLTNODE0.n3kgq4m0lhoednrx3hxtad2nha.cdmx.internal.cloudapp.net>
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- 17 Apr, 2026 4 commits
- 15 Apr, 2026 1 commit
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- 02 Apr, 2026 9 commits
- 01 Apr, 2026 7 commits
- 31 Mar, 2026 1 commit
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