GEMM custom op enablement#3046
Closed
samanamp wants to merge 1 commit into
Closed
Conversation
Summary: Inspired by the following medium article, wanted to implement block-wise benchmarking to see if are getting any perf gains. This diff, introduces block-wise as a custom op Differential Revision: D61800794
✅ Deploy Preview for pytorch-fbgemm-docs ready!
To edit notification comments on pull requests, go to your Netlify site configuration. |
Contributor
|
This pull request was exported from Phabricator. Differential Revision: D61800794 |
Contributor
|
This pull request has been merged in a9a3713. |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Summary: This diff adds custom op wrappers around
matmul_fp8_block. This should make them opaque to torch.compile and prevent issues where dynamo tries to trace triton code that is meant to be precompiled. I also add registration for fake kernels so that torch.compile can properly pass faketensors through the ops.Differential Revision: D61800794