mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-02-04 02:02:01 +08:00
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> |
||
|---|---|---|
| .. | ||
| _torch | ||
| api_stability | ||
| bindings | ||
| disaggregated | ||
| executor | ||
| llmapi | ||
| others | ||
| scaffolding | ||
| tools | ||
| trt | ||
| utils | ||
| conftest.py | ||
| dump_checkpoint_stats.py | ||
| gc_utils.py | ||
| profile_utils.py | ||
| pytest.ini | ||
| test_model_runner_cpp.py | ||
| test_pip_install.py | ||