ROCm OCP FP8 Support #1677
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ROCm OCP FP8 Support #1677
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February 6, 2025 10:30
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/1677
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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updates involve adding support for new ROCm versions and GPU architectures, updating data type handling, and removing outdated checks.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 ### Removal of Outdated Checks: * [`cmake/public/LoadHIP.cmake`](diffhunk://#diff-b98e27b9a5f196a6965a99ee5a7bb15b3fc633d6375b767635b1b04ccb2fd3d5L169-L197): Removed the check for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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Feb 24, 2025
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]>
added 2 commits
February 25, 2025 13:38
Add a comment documenting supported AMD GPU models and their corresponding LLVM gfx codes, including Navi4, MI300X, and MI350.
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Feb 27, 2025
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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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February 28, 2025 09:49
Use is_MI300() utility function to simplify MI300 architecture detection for float8 dtypes
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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. * [`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) * [`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. * [`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]>
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* document ROCm OCP F8 support * lint * Add AMD GPU model and gfx code documentation Add a comment documenting supported AMD GPU models and their corresponding LLVM gfx codes, including Navi4, MI300X, and MI350. * lint * Refactor MI300 float8 dtype detection using utility function Use is_MI300() utility function to simplify MI300 architecture detection for float8 dtypes * lint
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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]