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onnxruntime/cmake/external/cutlass.cmake

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CMake
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Remove USE_CUTLASS flag (#19271) ### Description Since Cutlass can be built with CUDA 11.4 (The minimum CUDA version for onnxruntime CUDA build), there is no need to have a flag to disable cutlass. Changes: (1) Reverted https://github.com/microsoft/onnxruntime/pull/18761 (2) remove the condition to build cutlass. (3) Fix a few build errors or warnings during testing CUDA 11.4 build. Note that SM 89 and 90 (including fp8) requires CUDA 11.8 or later. Flash attention and cutlass fused multihead attention will not be built for CUDA < 11.6. It is recommended to use CUDA 11.8 or above to build if you want to support latest GPUs. It is better to include it in 1.17.0 (otherwise, the release branch might encounter build failure with CUDA 11.4). Tests: (1) Build with flash attention and efficient attention off: **passed** (2) Build with CUDA 11.4: **passed** Example build command used in Ubuntu 20.04: ``` export CUDA_HOME=/usr/local/cuda-11.4 export CUDNN_HOME=/usr/lib/x86_64-linux-gnu/ export CUDACXX=/usr/local/cuda-11.4/bin/nvcc sh build.sh --config Release --build_shared_lib --parallel --use_cuda --cuda_version 11.4 \ --cuda_home $CUDA_HOME --cudnn_home $CUDNN_HOME --build_wheel --skip_tests \ --cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=80 \ --disable_types float8 ``` ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. -->
2024-01-26 00:57:58 +00:00
include(FetchContent)
Enable VCPKG in CI build (#23426) ### Description 1. Enable VCPKG flag in Windows CPU CI build pipelines. 2. Increased the min supported cmake version from 3.26 to 3.28. Because of it, drop the support for the old way of finding python by "find_package(PythonLibs)". Therefore, in build.py we no longer set "PYTHON_EXECUTABLE" cmake var when doing cmake configure. 3. Added "xnnpack-ep" as a feature for ORT's vcpkg config. 4. Added asset cache support for ORT's vcpkg build 5. Added VCPKG triplet files for Android build. 6. Set VCPKG triplet to "universal2-osx" if CMAKE_OSX_ARCHITECTURES was found in cmake extra defines. 7. Removed a small piece of code in build.py, which was for support CUDA version < 11.8. 8. Fixed an issue that CMAKE_OSX_ARCHITECTURES sometimes got specified twice when build.py invoked cmake. 9. Added more model tests to Android build. After this change, we will test all ONNX versions instead of just the latest one. 10. Fixed issues that are related to build.py's "--build_nuget" parameter. Also, enable the flag in most Windows CPU CI build jobs. 11. Removed a restriction in build.py that disallowed cross-compiling Windows ARM64 nuget package on Windows x86. ### Motivation and Context Adopt vcpkg.
2025-02-05 18:58:53 +00:00
onnxruntime_fetchcontent_declare(
Remove USE_CUTLASS flag (#19271) ### Description Since Cutlass can be built with CUDA 11.4 (The minimum CUDA version for onnxruntime CUDA build), there is no need to have a flag to disable cutlass. Changes: (1) Reverted https://github.com/microsoft/onnxruntime/pull/18761 (2) remove the condition to build cutlass. (3) Fix a few build errors or warnings during testing CUDA 11.4 build. Note that SM 89 and 90 (including fp8) requires CUDA 11.8 or later. Flash attention and cutlass fused multihead attention will not be built for CUDA < 11.6. It is recommended to use CUDA 11.8 or above to build if you want to support latest GPUs. It is better to include it in 1.17.0 (otherwise, the release branch might encounter build failure with CUDA 11.4). Tests: (1) Build with flash attention and efficient attention off: **passed** (2) Build with CUDA 11.4: **passed** Example build command used in Ubuntu 20.04: ``` export CUDA_HOME=/usr/local/cuda-11.4 export CUDNN_HOME=/usr/lib/x86_64-linux-gnu/ export CUDACXX=/usr/local/cuda-11.4/bin/nvcc sh build.sh --config Release --build_shared_lib --parallel --use_cuda --cuda_version 11.4 \ --cuda_home $CUDA_HOME --cudnn_home $CUDNN_HOME --build_wheel --skip_tests \ --cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=80 \ --disable_types float8 ``` ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. -->
2024-01-26 00:57:58 +00:00
cutlass
URL ${DEP_URL_cutlass}
URL_HASH SHA1=${DEP_SHA1_cutlass}
Enable VCPKG in CI build (#23426) ### Description 1. Enable VCPKG flag in Windows CPU CI build pipelines. 2. Increased the min supported cmake version from 3.26 to 3.28. Because of it, drop the support for the old way of finding python by "find_package(PythonLibs)". Therefore, in build.py we no longer set "PYTHON_EXECUTABLE" cmake var when doing cmake configure. 3. Added "xnnpack-ep" as a feature for ORT's vcpkg config. 4. Added asset cache support for ORT's vcpkg build 5. Added VCPKG triplet files for Android build. 6. Set VCPKG triplet to "universal2-osx" if CMAKE_OSX_ARCHITECTURES was found in cmake extra defines. 7. Removed a small piece of code in build.py, which was for support CUDA version < 11.8. 8. Fixed an issue that CMAKE_OSX_ARCHITECTURES sometimes got specified twice when build.py invoked cmake. 9. Added more model tests to Android build. After this change, we will test all ONNX versions instead of just the latest one. 10. Fixed issues that are related to build.py's "--build_nuget" parameter. Also, enable the flag in most Windows CPU CI build jobs. 11. Removed a restriction in build.py that disallowed cross-compiling Windows ARM64 nuget package on Windows x86. ### Motivation and Context Adopt vcpkg.
2025-02-05 18:58:53 +00:00
EXCLUDE_FROM_ALL
Remove USE_CUTLASS flag (#19271) ### Description Since Cutlass can be built with CUDA 11.4 (The minimum CUDA version for onnxruntime CUDA build), there is no need to have a flag to disable cutlass. Changes: (1) Reverted https://github.com/microsoft/onnxruntime/pull/18761 (2) remove the condition to build cutlass. (3) Fix a few build errors or warnings during testing CUDA 11.4 build. Note that SM 89 and 90 (including fp8) requires CUDA 11.8 or later. Flash attention and cutlass fused multihead attention will not be built for CUDA < 11.6. It is recommended to use CUDA 11.8 or above to build if you want to support latest GPUs. It is better to include it in 1.17.0 (otherwise, the release branch might encounter build failure with CUDA 11.4). Tests: (1) Build with flash attention and efficient attention off: **passed** (2) Build with CUDA 11.4: **passed** Example build command used in Ubuntu 20.04: ``` export CUDA_HOME=/usr/local/cuda-11.4 export CUDNN_HOME=/usr/lib/x86_64-linux-gnu/ export CUDACXX=/usr/local/cuda-11.4/bin/nvcc sh build.sh --config Release --build_shared_lib --parallel --use_cuda --cuda_version 11.4 \ --cuda_home $CUDA_HOME --cudnn_home $CUDNN_HOME --build_wheel --skip_tests \ --cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=80 \ --disable_types float8 ``` ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. -->
2024-01-26 00:57:58 +00:00
)
Add memory efficient attention from CUTLASS (#14343) ### Description Add memory efficient attention from CUTLASS. TODO (in next pull request): (1) Need performance tests on different GPUs, then add a sequence length threshold (only activate it for long sequence length). (2) Merge changes from https://github.com/NVIDIA/cutlass/pull/773 when it is in cutlass master.
2023-01-20 20:33:01 +00:00
Remove USE_CUTLASS flag (#19271) ### Description Since Cutlass can be built with CUDA 11.4 (The minimum CUDA version for onnxruntime CUDA build), there is no need to have a flag to disable cutlass. Changes: (1) Reverted https://github.com/microsoft/onnxruntime/pull/18761 (2) remove the condition to build cutlass. (3) Fix a few build errors or warnings during testing CUDA 11.4 build. Note that SM 89 and 90 (including fp8) requires CUDA 11.8 or later. Flash attention and cutlass fused multihead attention will not be built for CUDA < 11.6. It is recommended to use CUDA 11.8 or above to build if you want to support latest GPUs. It is better to include it in 1.17.0 (otherwise, the release branch might encounter build failure with CUDA 11.4). Tests: (1) Build with flash attention and efficient attention off: **passed** (2) Build with CUDA 11.4: **passed** Example build command used in Ubuntu 20.04: ``` export CUDA_HOME=/usr/local/cuda-11.4 export CUDNN_HOME=/usr/lib/x86_64-linux-gnu/ export CUDACXX=/usr/local/cuda-11.4/bin/nvcc sh build.sh --config Release --build_shared_lib --parallel --use_cuda --cuda_version 11.4 \ --cuda_home $CUDA_HOME --cudnn_home $CUDNN_HOME --build_wheel --skip_tests \ --cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=80 \ --disable_types float8 ``` ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. -->
2024-01-26 00:57:58 +00:00
FetchContent_GetProperties(cutlass)
if(NOT cutlass_POPULATED)
FetchContent_Populate(cutlass)
Add memory efficient attention from CUTLASS (#14343) ### Description Add memory efficient attention from CUTLASS. TODO (in next pull request): (1) Need performance tests on different GPUs, then add a sequence length threshold (only activate it for long sequence length). (2) Merge changes from https://github.com/NVIDIA/cutlass/pull/773 when it is in cutlass master.
2023-01-20 20:33:01 +00:00
endif()
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