Add option to build with CUDAToolkit and enable_language(CUDA) #336
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malfet
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Aug 15, 2022
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Sounds good to me, but I wonder how do you plan to test it
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I have pytorch/pytorch#83199 setup to build with my fork of gloo and with |
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I notice there's no build with CUDA 11 here. Maybe A new CI job for CUDA 11 with |
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@malfet I've got the CI job running. The build log shows: and also files show |
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Got internal approval, landing... |
pytorchmergebot
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Dec 8, 2022
With CUDA-10.2 gone we can finally do it! This PR mostly contains build system related changes, invasive functional ones are to be followed. Among many expected tweaks to the build system, here are few unexpected ones: - Force onnx_proto project to be updated to C++17 to avoid `duplicate symbols` error when compiled by gcc-7.5.0, as storage rule for `constexpr` changed in C++17, but gcc does not seem to follow it - Do not use `std::apply` on CUDA but rely on the built-in variant, as it results in test failures when CUDA runtime picks host rather than device function when `std::apply` is invoked from CUDA code. - `std::decay_t` -> `::std::decay_t` and `std::move`->`::std::move` as VC++ for some reason claims that `std` symbol is ambigious - Disable use of `std::aligned_alloc` on Android, as its `libc++` does not implement it. Some prerequisites: - #89297 - #89605 - #90228 - #90389 - #90379 - #89570 - pytorch/gloo#336 - pytorch/gloo#343 - pytorch/builder@919676f Fixes #56055 Pull Request resolved: #85969 Approved by: https://github.com/ezyang, https://github.com/kulinseth
kulinseth
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Dec 10, 2022
With CUDA-10.2 gone we can finally do it! This PR mostly contains build system related changes, invasive functional ones are to be followed. Among many expected tweaks to the build system, here are few unexpected ones: - Force onnx_proto project to be updated to C++17 to avoid `duplicate symbols` error when compiled by gcc-7.5.0, as storage rule for `constexpr` changed in C++17, but gcc does not seem to follow it - Do not use `std::apply` on CUDA but rely on the built-in variant, as it results in test failures when CUDA runtime picks host rather than device function when `std::apply` is invoked from CUDA code. - `std::decay_t` -> `::std::decay_t` and `std::move`->`::std::move` as VC++ for some reason claims that `std` symbol is ambigious - Disable use of `std::aligned_alloc` on Android, as its `libc++` does not implement it. Some prerequisites: - pytorch#89297 - pytorch#89605 - pytorch#90228 - pytorch#90389 - pytorch#90379 - pytorch#89570 - pytorch/gloo#336 - pytorch/gloo#343 - pytorch/builder@919676f Fixes pytorch#56055 Pull Request resolved: pytorch#85969 Approved by: https://github.com/ezyang, https://github.com/kulinseth
pruthvistony
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Dec 20, 2022
With CUDA-10.2 gone we can finally do it! This PR mostly contains build system related changes, invasive functional ones are to be followed. Among many expected tweaks to the build system, here are few unexpected ones: - Force onnx_proto project to be updated to C++17 to avoid `duplicate symbols` error when compiled by gcc-7.5.0, as storage rule for `constexpr` changed in C++17, but gcc does not seem to follow it - Do not use `std::apply` on CUDA but rely on the built-in variant, as it results in test failures when CUDA runtime picks host rather than device function when `std::apply` is invoked from CUDA code. - `std::decay_t` -> `::std::decay_t` and `std::move`->`::std::move` as VC++ for some reason claims that `std` symbol is ambigious - Disable use of `std::aligned_alloc` on Android, as its `libc++` does not implement it. Some prerequisites: - pytorch#89297 - pytorch#89605 - pytorch#90228 - pytorch#90389 - pytorch#90379 - pytorch#89570 - pytorch/gloo#336 - pytorch/gloo#343 - pytorch/builder@919676f Fixes pytorch#56055 Pull Request resolved: pytorch#85969 Approved by: https://github.com/ezyang, https://github.com/kulinseth
pruthvistony
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Jan 3, 2023
With CUDA-10.2 gone we can finally do it! This PR mostly contains build system related changes, invasive functional ones are to be followed. Among many expected tweaks to the build system, here are few unexpected ones: - Force onnx_proto project to be updated to C++17 to avoid `duplicate symbols` error when compiled by gcc-7.5.0, as storage rule for `constexpr` changed in C++17, but gcc does not seem to follow it - Do not use `std::apply` on CUDA but rely on the built-in variant, as it results in test failures when CUDA runtime picks host rather than device function when `std::apply` is invoked from CUDA code. - `std::decay_t` -> `::std::decay_t` and `std::move`->`::std::move` as VC++ for some reason claims that `std` symbol is ambigious - Disable use of `std::aligned_alloc` on Android, as its `libc++` does not implement it. Some prerequisites: - pytorch#89297 - pytorch#89605 - pytorch#90228 - pytorch#90389 - pytorch#90379 - pytorch#89570 - pytorch/gloo#336 - pytorch/gloo#343 - pytorch/builder@919676f Fixes pytorch#56055 Pull Request resolved: pytorch#85969 Approved by: https://github.com/ezyang, https://github.com/kulinseth
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find_package(CUDA)is deprecated in newer versions of cmake. This adds theGLOO_USE_CUDA_TOOLKIToption to build withenable_language(CUDA)andfind_package(CUDAToolkit)which are the modern cmake replacements.cc @malfet