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fd4311e6a3
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> |
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| attention | ||
| auto_deploy | ||
| compilation | ||
| debugger | ||
| executor | ||
| misc | ||
| modeling | ||
| models/checkpoints/hf | ||
| modules | ||
| multi_gpu | ||
| multi_gpu_modeling | ||
| multimodal | ||
| sampler | ||
| speculative | ||
| thop | ||
| helpers.py | ||
| pattern_watcher.py | ||
| test_connector.py | ||