[BE] Delete BUILD_SPLIT_CUDA option #87502
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As we are linking with cuDNN dynamically anyway, we no longer approaching 2Gb binary size limit, so BUILD_SPLIT_CUDA can go away.
malfet
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a team,
fmassa,
soumith and
ezyang
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/87502
Note: Links to docs will display an error until the docs builds have been completed. ❌ 1 Failures, 4 PendingAs of commit 442789f: The following jobs have failed:
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atalman
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Oct 21, 2022
janeyx99
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Oct 21, 2022
malfet
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@pytorchbot merge -f "Tests are flaky" |
Merge startedYour change will be merged immediately since you used the force (-f) flag, bypassing any CI checks (ETA: 1-5 minutes). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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Hey @malfet. |
sgrigory
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Oct 28, 2022
As we are linking with cuDNN and cuBLAS dynamically for all configs anyway, as statically linked cuDNN is different library than dynamically linked one, increases default memory footprint, etc, and libtorch_cuda even if compiled for all GPU architectures is no longer approaching 2Gb binary size limit, so BUILD_SPLIT_CUDA can go away. Pull Request resolved: pytorch#87502 Approved by: https://github.com/atalman
jjsjann123
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Oct 29, 2022
As we are linking with cuDNN and cuBLAS dynamically for all configs anyway, as statically linked cuDNN is different library than dynamically linked one, increases default memory footprint, etc, and libtorch_cuda even if compiled for all GPU architectures is no longer approaching 2Gb binary size limit, so BUILD_SPLIT_CUDA can go away. Pull Request resolved: pytorch/pytorch#87502 Approved by: https://github.com/atalman
kulinseth
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Nov 5, 2022
As we are linking with cuDNN and cuBLAS dynamically for all configs anyway, as statically linked cuDNN is different library than dynamically linked one, increases default memory footprint, etc, and libtorch_cuda even if compiled for all GPU architectures is no longer approaching 2Gb binary size limit, so BUILD_SPLIT_CUDA can go away. Pull Request resolved: pytorch#87502 Approved by: https://github.com/atalman
jjsjann123
pushed a commit
to jjsjann123/nvfuser
that referenced
this pull request
Nov 10, 2022
As we are linking with cuDNN and cuBLAS dynamically for all configs anyway, as statically linked cuDNN is different library than dynamically linked one, increases default memory footprint, etc, and libtorch_cuda even if compiled for all GPU architectures is no longer approaching 2Gb binary size limit, so BUILD_SPLIT_CUDA can go away. Pull Request resolved: pytorch/pytorch#87502 Approved by: https://github.com/atalman
kulinseth
pushed a commit
to kulinseth/pytorch
that referenced
this pull request
Dec 10, 2022
As we are linking with cuDNN and cuBLAS dynamically for all configs anyway, as statically linked cuDNN is different library than dynamically linked one, increases default memory footprint, etc, and libtorch_cuda even if compiled for all GPU architectures is no longer approaching 2Gb binary size limit, so BUILD_SPLIT_CUDA can go away. Pull Request resolved: pytorch#87502 Approved by: https://github.com/atalman
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As we are linking with cuDNN and cuBLAS dynamically for all configs anyway, as statically linked cuDNN is different library than dynamically linked one, increases default memory footprint, etc, and libtorch_cuda even if compiled for all GPU architectures is no longer approaching 2Gb binary size limit, so BUILD_SPLIT_CUDA can go away.