MOLEDGL nvmath+cuBLAS backend#1983
Open
maxwelltsai wants to merge 3 commits into
Open
Conversation
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
This PR implements a new
dglbackend for MOLEDGL. When runningfairchemwith arunner.candidate_overrides=["moe_layer_type=dgl"]override, the linear ops in MOLEDGL will be dispatched to cuBLAS via thenvmath-pythonpackage. This aims to replace thefairchem_cppbranch and make the code compilation-free.fairchem.core.common.segmentmmis the main driver that encapsulates the cuBLAS GEMM ops as python functions, which makes them directly callable from the model.This PR also introduces an optional kwarg in
MOLEDGL.forward(..., use_grouped_gemm=..., ), which controls whether the batch should be dispatched tocublasGemmEx()orcublasGemmGroupedBatchedEx()(optimal performance of using either one depends on the batch shape).