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Make AVX Support Optional (#1698) by excelle08 · Pull Request #1795 · pytorch/FBGEMM · GitHub
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Summary:

  • Add FindAVX.cmake from the PyTorch project to detect AVX compilation flags and conditionally add them to FBGEMM_GPU targets

Test Plan:
On a devarm machine:

  • Set up the environment according to the building instruction. For convenience we can source .github/scripts/setup_env.bash in the FBGEMM repo and run the functions in it.
  • Build and install CPU-only variant of fbgemm_gpu:
    # Assuming the CWD is the FBGEMM repo directory and setup_env.bash is sourced
    cd fbgemm_gpu
    build_fbgemm_gpu_install cpu
    Example log of a a successful building and installing process is like this: P717846260
  • Run tests: run_fbgemm_gpu_tests mycondaenv cpu under fbgemm_gpu/tests directory

Differential Revision: D45139063

Pulled By: excelle08

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This pull request was exported from Phabricator. Differential Revision: D45139063

excelle08 pushed a commit to excelle08/FBGEMM that referenced this pull request May 31, 2023
Summary:
Pull Request resolved: pytorch#1795

- Add `FindAVX.cmake` from the PyTorch project to detect AVX compilation flags and conditionally add them to FBGEMM_GPU targets

Pull Request resolved: pytorch#1698

Test Plan:
On a devarm machine:
- Set up the environment according to [the building instruction](https://github.com/pytorch/FBGEMM/blob/main/fbgemm_gpu/docs/BuildInstructions.md). For convenience we can source `.github/scripts/setup_env.bash` in the FBGEMM repo and run the functions in it.
- Build and install CPU-only variant of fbgemm_gpu:
      # Assuming the CWD is the FBGEMM repo directory and setup_env.bash is sourced
      cd fbgemm_gpu
      build_fbgemm_gpu_install <conda-env-name> cpu
Example log of a a successful building and installing process is like this: P717846260
- Run tests: `run_fbgemm_gpu_tests mycondaenv cpu` under `fbgemm_gpu/tests` directory

Differential Revision: D45139063

Pulled By: excelle08

fbshipit-source-id: 35a1b605ee8503c5eb85783ca4b55030d296abc8
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This pull request was exported from Phabricator. Differential Revision: D45139063

excelle08 pushed a commit to excelle08/FBGEMM that referenced this pull request Jun 1, 2023
Summary:
Pull Request resolved: pytorch#1795

- Add `FindAVX.cmake` from the PyTorch project to detect AVX compilation flags and conditionally add them to FBGEMM_GPU targets

Pull Request resolved: pytorch#1698

Test Plan:
On a devarm machine:
- Set up the environment according to [the building instruction](https://github.com/pytorch/FBGEMM/blob/main/fbgemm_gpu/docs/BuildInstructions.md). For convenience we can source `.github/scripts/setup_env.bash` in the FBGEMM repo and run the functions in it.
- Build and install CPU-only variant of fbgemm_gpu:
      # Assuming the CWD is the FBGEMM repo directory and setup_env.bash is sourced
      cd fbgemm_gpu
      build_fbgemm_gpu_install <conda-env-name> cpu
Example log of a a successful building and installing process is like this: P717846260
- Run tests: `run_fbgemm_gpu_tests mycondaenv cpu` under `fbgemm_gpu/tests` directory

Reviewed By: q10

Differential Revision: D45139063

Pulled By: excelle08

fbshipit-source-id: 561ccf4ef5eb7778ea6a3443b2f604216fb4542b
@facebook-github-bot
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This pull request was exported from Phabricator. Differential Revision: D45139063

excelle08 pushed a commit to excelle08/FBGEMM that referenced this pull request Jun 1, 2023
Summary:
Pull Request resolved: pytorch#1795

- Add `FindAVX.cmake` from the PyTorch project to detect AVX compilation flags and conditionally add them to FBGEMM_GPU targets

Pull Request resolved: pytorch#1698

Test Plan:
On a devarm machine:
- Set up the environment according to [the building instruction](https://github.com/pytorch/FBGEMM/blob/main/fbgemm_gpu/docs/BuildInstructions.md). For convenience we can source `.github/scripts/setup_env.bash` in the FBGEMM repo and run the functions in it.
- Build and install CPU-only variant of fbgemm_gpu:
      # Assuming the CWD is the FBGEMM repo directory and setup_env.bash is sourced
      cd fbgemm_gpu
      build_fbgemm_gpu_install <conda-env-name> cpu
Example log of a a successful building and installing process is like this: P717846260
- Run tests: `run_fbgemm_gpu_tests mycondaenv cpu` under `fbgemm_gpu/tests` directory

Reviewed By: q10

Differential Revision: D45139063

Pulled By: excelle08

fbshipit-source-id: 86b5cc55c33861f09265746dda7427359a4db3e0
@facebook-github-bot
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This pull request was exported from Phabricator. Differential Revision: D45139063

excelle08 pushed a commit to excelle08/FBGEMM that referenced this pull request Jun 1, 2023
Summary:
Pull Request resolved: pytorch#1795

- Add `FindAVX.cmake` from the PyTorch project to detect AVX compilation flags and conditionally add them to FBGEMM_GPU targets

Pull Request resolved: pytorch#1698

Test Plan:
On a devarm machine:
- Set up the environment according to [the building instruction](https://github.com/pytorch/FBGEMM/blob/main/fbgemm_gpu/docs/BuildInstructions.md). For convenience we can source `.github/scripts/setup_env.bash` in the FBGEMM repo and run the functions in it.
- Build and install CPU-only variant of fbgemm_gpu:
      # Assuming the CWD is the FBGEMM repo directory and setup_env.bash is sourced
      cd fbgemm_gpu
      build_fbgemm_gpu_install <conda-env-name> cpu
Example log of a a successful building and installing process is like this: P717846260
- Run tests: `run_fbgemm_gpu_tests mycondaenv cpu` under `fbgemm_gpu/tests` directory

Reviewed By: q10

Differential Revision: D45139063

Pulled By: excelle08

fbshipit-source-id: d9f6660d84d6ed6add3742ecb58ee18c37d2591a
@facebook-github-bot
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Contributor

This pull request was exported from Phabricator. Differential Revision: D45139063

excelle08 pushed a commit to excelle08/FBGEMM that referenced this pull request Jun 1, 2023
Summary:
Pull Request resolved: pytorch#1795

- Add `FindAVX.cmake` from the PyTorch project to detect AVX compilation flags and conditionally add them to FBGEMM_GPU targets

Pull Request resolved: pytorch#1698

Test Plan:
On a devarm machine:
- Set up the environment according to [the building instruction](https://github.com/pytorch/FBGEMM/blob/main/fbgemm_gpu/docs/BuildInstructions.md). For convenience we can source `.github/scripts/setup_env.bash` in the FBGEMM repo and run the functions in it.
- Build and install CPU-only variant of fbgemm_gpu:
      # Assuming the CWD is the FBGEMM repo directory and setup_env.bash is sourced
      cd fbgemm_gpu
      build_fbgemm_gpu_install <conda-env-name> cpu
Example log of a a successful building and installing process is like this: P717846260
- Run tests: `run_fbgemm_gpu_tests mycondaenv cpu` under `fbgemm_gpu/tests` directory

Reviewed By: q10

Differential Revision: D45139063

Pulled By: excelle08

fbshipit-source-id: fa1c1065888630dc1e9b8ec84e4493be3565596e
@facebook-github-bot
Copy link
Contributor

This pull request was exported from Phabricator. Differential Revision: D45139063

Summary:
Pull Request resolved: pytorch#1795

- Add `FindAVX.cmake` from the PyTorch project to detect AVX compilation flags and conditionally add them to FBGEMM_GPU targets

Pull Request resolved: pytorch#1698

Test Plan:
On a devarm machine:
- Set up the environment according to [the building instruction](https://github.com/pytorch/FBGEMM/blob/main/fbgemm_gpu/docs/BuildInstructions.md). For convenience we can source `.github/scripts/setup_env.bash` in the FBGEMM repo and run the functions in it.
- Build and install CPU-only variant of fbgemm_gpu:
      # Assuming the CWD is the FBGEMM repo directory and setup_env.bash is sourced
      cd fbgemm_gpu
      build_fbgemm_gpu_install <conda-env-name> cpu
Example log of a a successful building and installing process is like this: P717846260
- Run tests: `run_fbgemm_gpu_tests mycondaenv cpu` under `fbgemm_gpu/tests` directory

Reviewed By: q10

Differential Revision: D45139063

Pulled By: excelle08

fbshipit-source-id: fe841aa6321881c7e7d76da8400f3d6eb0354b2e
@facebook-github-bot
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This pull request was exported from Phabricator. Differential Revision: D45139063

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@excelle08 merged this pull request in 323afc5.

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3 participants