ROCm OCP FP8 Support #1677
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ROCm OCP FP8 Support #1677
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/1677
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 475d2f5 with merge base ea7910e ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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topic: improvement
vkuzo
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Feb 6, 2025
| for arch in mxArchName: | ||
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| def is_MI350(): |
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optional: if there is any public info (spec sheet, etc) we can link to about this hardware from the docblock, I think that would be awesome! same for below.
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thanks . I've added Supported AMD GPU Models and their LLVM gfx Codes
will add detail documentation when the time is right.
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TLDR: Follow up/ Build on top of #144476. add OCP FP8 support for gfx950 refer to pytorch/ao#1677 This pull request includes several changes to improve compatibility and support for new GPU architectures and data types, particularly for ROCm. The key updates involve adding support for new ROCm versions and GPU architectures, updating data type handling, and removing outdated checks. ### Improvements to GPU Architecture and ROCm Version Support: * [`aten/src/ATen/Context.cpp`](diffhunk://#diff-33de472d304acbe57d693c8567370c638068bedc1aa0ce8e9dc115dad05a7810L323-R326): Added support for new GPU architectures `gfx1200`, `gfx1201`, and `gfx950` based on ROCm version checks. * [`aten/src/ATen/native/cuda/Blas.cpp`](diffhunk://#diff-e8a569efee1e650172f120a0fdcda024fe3e4703a4ee3336425c8f685af6b3abL196-R199): Updated architecture support in multiple functions to include `gfx1200`, `gfx1201`, and `gfx950` based on ROCm version checks. [[1]](diffhunk://#diff-e8a569efee1e650172f120a0fdcda024fe3e4703a4ee3336425c8f685af6b3abL196-R199) [[2]](diffhunk://#diff-e8a569efee1e650172f120a0fdcda024fe3e4703a4ee3336425c8f685af6b3abL865-R876) ### Updates to Data Type Handling: * [`aten/src/ATen/cuda/CUDADataType.h`](diffhunk://#diff-9188bb13b1a49f459141f5f9b875593d1c5ce2beb5ad711fdbaf5bc7089ec015L81-L98): Enhanced data type conversion to include new float8 types for both CUDA and ROCm environments. * [`aten/src/ATen/cuda/tunable/GemmHipblaslt.h`](diffhunk://#diff-bfa1a3b5d4bef1892bf50338775f3b0fd8cd31fc1868148f3968b98aefb68e3fL29-R80): Updated `HipDataTypeFor` template to handle new float8 types and added hard-coded enum values for ROCm versions prior to 6.3. ### Removal of Outdated Checks: * [`cmake/public/LoadHIP.cmake`](diffhunk://#diff-b98e27b9a5f196a6965a99ee5a7bb15b3fc633d6375b767635b1b04ccb2fd3d5L169-L197): Removed the check for `HIP_NEW_TYPE_ENUMS` as it is no longer necessary with the updated ROCm versions. [[1]](diffhunk://#diff-b98e27b9a5f196a6965a99ee5a7bb15b3fc633d6375b767635b1b04ccb2fd3d5L169-L197) [[2]](diffhunk://#diff-b98e27b9a5f196a6965a99ee5a7bb15b3fc633d6375b767635b1b04ccb2fd3d5L211-R182) These changes ensure better compatibility and performance on newer hardware and software environments, particularly for users leveraging ROCm and CUDA for deep learning and scientific computing tasks. Pull Request resolved: #146632 Approved by: https://github.com/jeffdaily Co-authored-by: Jeff Daily <[email protected]>
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TLDR: Follow up/ Build on top of pytorch#144476. add OCP FP8 support for gfx950 refer to pytorch/ao#1677 This pull request includes several changes to improve compatibility and support for new GPU architectures and data types, particularly for ROCm. The key updates involve adding support for new ROCm versions and GPU architectures, updating data type handling, and removing outdated checks. ### Improvements to GPU Architecture and ROCm Version Support: * [`aten/src/ATen/Context.cpp`](diffhunk://#diff-33de472d304acbe57d693c8567370c638068bedc1aa0ce8e9dc115dad05a7810L323-R326): Added support for new GPU architectures `gfx1200`, `gfx1201`, and `gfx950` based on ROCm version checks. * [`aten/src/ATen/native/cuda/Blas.cpp`](diffhunk://#diff-e8a569efee1e650172f120a0fdcda024fe3e4703a4ee3336425c8f685af6b3abL196-R199): Updated architecture support in multiple functions to include `gfx1200`, `gfx1201`, and `gfx950` based on ROCm version checks. [[1]](diffhunk://#diff-e8a569efee1e650172f120a0fdcda024fe3e4703a4ee3336425c8f685af6b3abL196-R199) [[2]](diffhunk://#diff-e8a569efee1e650172f120a0fdcda024fe3e4703a4ee3336425c8f685af6b3abL865-R876) ### Updates to Data Type Handling: * [`aten/src/ATen/cuda/CUDADataType.h`](diffhunk://#diff-9188bb13b1a49f459141f5f9b875593d1c5ce2beb5ad711fdbaf5bc7089ec015L81-L98): Enhanced data type conversion to include new float8 types for both CUDA and ROCm environments. * [`aten/src/ATen/cuda/tunable/GemmHipblaslt.h`](diffhunk://#diff-bfa1a3b5d4bef1892bf50338775f3b0fd8cd31fc1868148f3968b98aefb68e3fL29-R80): Updated `HipDataTypeFor` template to handle new float8 types and added hard-coded enum values for ROCm versions prior to 6.3. ### Removal of Outdated Checks: * [`cmake/public/LoadHIP.cmake`](diffhunk://#diff-b98e27b9a5f196a6965a99ee5a7bb15b3fc633d6375b767635b1b04ccb2fd3d5L169-L197): Removed the check for `HIP_NEW_TYPE_ENUMS` as it is no longer necessary with the updated ROCm versions. [[1]](diffhunk://#diff-b98e27b9a5f196a6965a99ee5a7bb15b3fc633d6375b767635b1b04ccb2fd3d5L169-L197) [[2]](diffhunk://#diff-b98e27b9a5f196a6965a99ee5a7bb15b3fc633d6375b767635b1b04ccb2fd3d5L211-R182) These changes ensure better compatibility and performance on newer hardware and software environments, particularly for users leveraging ROCm and CUDA for deep learning and scientific computing tasks. Pull Request resolved: pytorch#146632 Approved by: https://github.com/jeffdaily Co-authored-by: Jeff Daily <[email protected]>
Add a comment documenting supported AMD GPU models and their corresponding LLVM gfx codes, including Navi4, MI300X, and MI350.
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TLDR: Quick fix for ROCm device check. OCP FP8 support status update.
This pull request includes changes to improve the handling of imports, update configurations, and add new utility functions in the
torchaolibrary. The most important changes include removing comments to avoid circular imports, updating the configuration for supported float8 types, and adding utility functions to check for specific GPU architectures.refer to : pytorch/pytorch#146632
Configuration updates:
torchao/float8/config.py: Updated the configuration for selecting the preferred float8 type pair to include support for OCP F8 variants in MI350/Navi4.New utility functions:
torchao/utils.py: Added new utility functionsis_MI350andis_Navi4to check for specific GPU architectures.Improvements to import handling:
torchao/dtypes/uintx/marlin_qqq_tensor.py: Removed comments to avoid circular imports in the__tensor_unflatten__andfrom_plainmethods. [1] [2]torchao/dtypes/uintx/marlin_sparse_layout.py: Removed comments to avoid circular imports in the__tensor_unflatten__andfrom_plainmethods. [1] [2]