⚡️ Improve SequenceSet#xor performance by ~2x
#463
Closed
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
Obviously, the performance improvement is highly dependant on what data you're using, whether YJIT is enabled, etc. I saw results ranging from 1.7x faster to 2.6x faster. The benchmark script is included. For a benchmark run using sets with 10k members: ``` new impl 79.061 (± 8.9%) i/s (12.65 ms/i) - 392.000 in 5.004322s old impl 32.736 (±15.3%) i/s (30.55 ms/i) - 162.000 in 5.052839s ``` The old implementation was ~2.42x slower. For a benchmark run using very sparse sets with 100 members: ``` new impl 4.295k (±13.5%) i/s (232.81 μs/i) - 21.476k in 5.102536s old impl 2.459k (±11.3%) i/s (406.69 μs/i) - 12.095k in 5.000148s ``` This time, the old implementation was ~1.75x slower. I have some other (much bigger) PRs that should give even bigger performance improvements, but this is simple and effective.
|
I didn't have proper tests over |
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Outdated suggestions cannot be applied.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.
Obviously, the performance improvement is highly dependant on what data you're using, whether YJIT is enabled, etc. I saw results ranging from 1.5x faster to 2.7x faster. The benchmark script is included.
For a benchmark run using sets with 10k members:
The old implementation was ~2.42x slower.
For a benchmark run using very sparse sets with 100 members:
This time, the old implementation was ~1.75x slower.
I have some other (much bigger) PRs that should give even bigger performance (and memory use) improvements, but this is simple and effective.