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2225745782
Because we have encountered some perf regression due to using a one-shot kernel instead of NCCL on A100/H100, it will be beneficial if we can have a solid benchmarking of allreduce Op and analyze the data collected from it. Implemented new AllreduceOp heuristic: - Added Linear programming-based heuristic implementation. - Added LUT-based heuristic implementation and corresponding code generation script. AllreduceOp minor fixing: - Fixed a minor issue in AllreduceOp, that the strategy can not be overridden when ONESHOT or TWOSHOT is set. - Fixed a minor TWOSHOT kernel perf issue. - Cleaned up Dispatching code in AllReduceOp. This PR will fix the perf gaps reported in: https://nvbugspro.nvidia.com/bug/5517023 For Deepseek-R1, it shows a performance gain of about 3-4% in concurrency levels of 256 and 512. Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com> Signed-off-by: Mike Iovine <6158008+mikeiovine@users.noreply.github.com> |
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| .. | ||
| test_allreduce.py | ||
| test_alltoall.py | ||
| test_ar_residual_norm.py | ||
| test_embedding.py | ||
| test_linear.py | ||
| test_lowprecision_allreduce.py | ||
| test_mnnvl_allreduce.py | ||
| test_mnnvl_memory.py | ||
| test_moe_a2a.py | ||
| test_star_attention_input.jsonl | ||
| test_star_attention.py | ||
| test_user_buffers.py | ||