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@ngimel ngimel commented Mar 10, 2022

Summary: Disables cublasLt as it is buggy with cuda 11.0. We'll reenable it based on cuda version (some known bugs are fixed in 11.5)

Test Plan: Existing tests

Differential Revision: D34775050

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This pull request was exported from Phabricator. Differential Revision: D34775050

Summary:
Pull Request resolved: pytorch#74021

Disables cublasLt as it is buggy with cuda 11.0. We'll reenable it based on cuda version (some known bugs are fixed in 11.5)

Test Plan: Existing tests

Reviewed By: jspark1105

Differential Revision: D34775050

fbshipit-source-id: 6931db465c98c452ec3cc49947de9daeb4ce0465
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This pull request was exported from Phabricator. Differential Revision: D34775050

@ngimel ngimel force-pushed the export-D34775050 branch from 514fa4a to 2ed8c19 Compare March 10, 2022 18:17
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ngimel commented Mar 10, 2022

I'm guarding use of cublasLt on cuda version 11.4, and I've removed "batch size" condition, because we are doing matrix multiply (not batched matrix multiply), so batch limitation doesn't apply (this still might have some perf issues though, we also need to specify workspace)
@xwang233 can you please work on a PR adding workspace and benchmark it to make sure that regressions like #73328 don't happen? This PR will cause #73328 regression again because I removed mat0 size check.

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Hi @ngimel , isn't cublaslt workspace size already added in #73439, or do you want it be 4 MB?

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ngimel commented Mar 10, 2022

Oh right, I missed it. @xwang233 if you know of any additional conditions that should be used to determine whether to use cublasLt, or if you could do more thorough testing with cuda 11.5 to make sure there's no regression in functionality and perf, that would be great.

facebook-github-bot pushed a commit that referenced this pull request Mar 10, 2022
Summary:
Pull Request resolved: #74021

Disables cublasLt as it is buggy with cuda 11.0. We'll reenable it based on cuda version (some known bugs are fixed in 11.5)

Test Plan: Existing tests

Reviewed By: jspark1105

Differential Revision: D34775050

fbshipit-source-id: 3faf3d15a0d9e24ca99e3ab515d2bc73a4c51fb5
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Hey @ngimel.
You've committed this PR, but it does not have both a 'release notes: ...' and 'topics: ...' label. Please add one of each to the PR. The 'release notes: ...' label should represent the part of PyTorch that this PR changes (fx, autograd, distributed, etc) and the 'topics: ...' label should represent the kind of PR it is (not user facing, new feature, bug fix, perf improvement, etc). The list of valid labels can be found here for the 'release notes: ...' and here for the 'topics: ...'.
For changes that are 'topic: not user facing' there is no need for a release notes label.

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