Basic parallelism machinery #195
Merged
Conversation
This file contains 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
So I can play around with parser parallelization. On my desktop, this simple thing is actually a little faster than coreutils wc (4.76 sec vs. 4.21 sec to process the arabidopsis GAF).
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Outdated suggestions cannot be applied.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.
Baby's first Rayon experiment. I tried parallelizing the basic memchr iteration—not for anything important, just for a really basic
wc -l(text-file line count) implementation.fgfa bench --wcl foo.txtshould count the number of lines in the file. This is just a demo to see what it could do; it is not actually useful.Anyway, the perf results are confusing, at the moment. On my MacBook Pro,
wc -litself takes 8.0 seconds to process the big Arabidopsis GAF; the sequential line counter takes 8.7 seconds (seems about right), and the parallel version takes 0.25 seconds (seems way too fast). (They all get the same answer.) This does not make much sense; why would the parallel version be 35 times faster? It's only a 10-core machine. Is it MLP, maybe? Weird effects of splitting up thememchrwork into smaller chunks? It's a mystery. I guess I will try applying this to the actual GAF parser next to see what happens.