Use thrust::binary_search to verify negative samples on GPU#524
Merged
Conversation
Use thrust::binary_search to verify negative samples on the GPU instead of
doing a linear scan in the BPR model.
This leads to a noticeable perf increase on larger datasets. For instance on the
Github stars dataset:
* Using linear_search: 3.09s/it
* using thrust::binary_search 1.53s/it
* w/ verify_negative_samples=False 1.18s/it
This change doubles the BPR training performance on that dataset, and also
leads to times that are only 30% slower than not verifying samples at all.
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
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
Use thrust::binary_search to verify negative samples on the GPU instead of
doing a linear scan in the BPR model.
This leads to a noticeable perf increase on larger datasets. For instance on the
Github stars dataset:
* Using linear_search: 3.09s/it
* using thrust::binary_search 1.53s/it
* w/ verify_negative_samples=False 1.18s/it
This change doubles the BPR training performance on that dataset, and also
leads to times that are only 30% slower than not verifying samples at all.