[SymmetricMemoryOps] implement one_shot_all_reduce #137472
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/137472
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 2dfe6d8 with merge base 9b2e453 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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I assume you've benchmarked this?
weifengpy
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## This Stack Implement custom all-reduce algos available in `IntraNodeComm` as `symm_mem` ops and replace the existing `IntraNodeComm` kernels with them. ## This PR Implement `symm_mem::two_shot_all_reduce_`. Later we'll replace the two-shot all-reduce in `IntraNodeComm` with these. Pull Request resolved: #137473 Approved by: https://github.com/Chillee ghstack dependencies: #137471, #137472
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…reduce (#137474) ## This Stack Implement custom all-reduce algos available in `IntraNodeComm` as `symm_mem` ops and replace the existing `IntraNodeComm` kernels with them. ## This PR Implement `symm_mem::multimem_one_shot_all_reduce_out`. The out-variant is more suitable for `IntraNodeComm` integration. Pull Request resolved: #137474 Approved by: https://github.com/Chillee ghstack dependencies: #137471, #137472, #137473
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…m ops (#137475) ## This Stack Implement custom all-reduce algos available in `IntraNodeComm` as `symm_mem` ops and replace the existing `IntraNodeComm` kernels with them. ## This PR - Replaces one-shot all-reduce with `symm_mem::one_shot_all_reduce_out` - Replaces two-shot all-reduce with `symm_mem::two_shot_all_reduce_` - Removes HCM all-reduce (at least for now). Due to the nature of its accumulation order, we can't guarantee the numerical consistency across all ranks. - Removes the `IntraNodeComm` python binding (its original purpose is superceded by `SymmetricMemory`). - Removes methods that were made for the python binding. - Replaces nvlink detection logic with `DMAConnectivityDetector`. Pull Request resolved: #137475 Approved by: https://github.com/Chillee ghstack dependencies: #137471, #137472, #137473, #137474
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…ating bfloat16 with multimem.ld_reduce (#137529) This provides better accuracy without additional cost. Also added documentation to `multimem_one_shot_all_reduce` to note the numerical caveats. Pull Request resolved: #137529 Approved by: https://github.com/Chillee ghstack dependencies: #137471, #137472, #137473, #137474, #137475
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- Previously the detection would fail before user calling APIs such as `torch.cuda.set_device()`. This is because the detection logic requires nvml initialization. In this PR, we added explicit nvml initialization (which idempotent). - Previously any nvml issue occurred in the detection logic would result in fatal error. Now we issue an informative warning and return a topology assuming no NVLink connectivity. Pull Request resolved: #137530 Approved by: https://github.com/Chillee ghstack dependencies: #137471, #137472, #137473, #137474, #137475, #137529
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ghstack-source-id: 6dbadcb Pull Request resolved: pytorch#137472
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Hi @yifuwang , do you know why pytorch only support fp32 and bf16 for multimem based AR? Why PyTorch decided to drop fp16 / fp8_e4m3 / fp8e5m2 for now? Thanks~ |
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Stack from ghstack (oldest at bottom):
This Stack
Implement custom all-reduce algos available in
IntraNodeCommassymm_memops and replace the existingIntraNodeCommkernels with them.This PR
Implement
symm_mem::one_shot_all_reduceandsymm_mem::one_shot_all_reduce_out. Later we'll replace the one-shot all-reduce inIntraNodeCommwith these.cc @XilunWu @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o