-
Notifications
You must be signed in to change notification settings - Fork 226
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
implements weighted shuffle using N-ary tree #259
implements weighted shuffle using N-ary tree #259
Conversation
f0b4ac2
to
55d94d1
Compare
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## master #259 +/- ##
=========================================
- Coverage 81.9% 81.9% -0.1%
=========================================
Files 840 840
Lines 228105 228102 -3
=========================================
- Hits 186837 186832 -5
- Misses 41268 41270 +2 |
This is port of firedancer's implementation of weighted shuffle: https://github.com/firedancer-io/firedancer/blob/3401bfc26/src/ballet/wsample/fd_wsample.c anza-xyz#185 implemented weighted shuffle using binary tree. Though asymptotically a binary tree has better performance, compared to a Fenwick tree, it is less cache local resulting in smaller improvements and in particular slower WeightedShuffle::new. In order to improve cache locality and reduce the overheads of traversing the tree, this commit instead uses a generalized N-ary tree with fanout of 16, showing significant improvements in both WeightedShuffle::new and WeightedShuffle::shuffle. With 4000 weights: N-ary tree (fanout 16): test bench_weighted_shuffle_new ... bench: 36,244 ns/iter (+/- 243) test bench_weighted_shuffle_shuffle ... bench: 149,082 ns/iter (+/- 1,474) Binary tree: test bench_weighted_shuffle_new ... bench: 58,514 ns/iter (+/- 229) test bench_weighted_shuffle_shuffle ... bench: 269,961 ns/iter (+/- 16,446) Fenwick tree: test bench_weighted_shuffle_new ... bench: 39,413 ns/iter (+/- 179) test bench_weighted_shuffle_shuffle ... bench: 364,771 ns/iter (+/- 2,078) The improvements become even more significant as there are more items to shuffle. With 20_000 weights: N-ary tree (fanout 16): test bench_weighted_shuffle_new ... bench: 200,659 ns/iter (+/- 4,395) test bench_weighted_shuffle_shuffle ... bench: 941,928 ns/iter (+/- 26,492) Binary tree: test bench_weighted_shuffle_new ... bench: 881,114 ns/iter (+/- 12,343) test bench_weighted_shuffle_shuffle ... bench: 1,822,257 ns/iter (+/- 12,772) Fenwick tree: test bench_weighted_shuffle_new ... bench: 276,936 ns/iter (+/- 14,692) test bench_weighted_shuffle_shuffle ... bench: 2,644,713 ns/iter (+/- 49,252)
55d94d1
to
e8e5583
Compare
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
those performance numbers look great! why did you settle on FANOUT of 16? just performed the best when you tested or?? Looks like firedancer is using 9. either way lgtm!
yeah, ran the benchmarks with different values of |
Backports to the beta branch are to be avoided unless absolutely necessary for fixing bugs, security issues, and perf regressions. Changes intended for backport should be structured such that a minimum effective diff can be committed separately from any refactoring, plumbing, cleanup, etc that are not strictly necessary to achieve the goal. Any of the latter should go only into master and ride the normal stabilization schedule. Exceptions include CI/metrics changes, CLI improvements and documentation updates on a case by case basis. |
This is port of firedancer's implementation of weighted shuffle: https://github.com/firedancer-io/firedancer/blob/3401bfc26/src/ballet/wsample/fd_wsample.c #185 implemented weighted shuffle using binary tree. Though asymptotically a binary tree has better performance, compared to a Fenwick tree, it has less cache locality resulting in smaller improvements and in particular slower WeightedShuffle::new. In order to improve cache locality and reduce the overheads of traversing the tree, this commit instead uses a generalized N-ary tree with fanout of 16, showing significant improvements in both WeightedShuffle::new and WeightedShuffle::shuffle. With 4000 weights: N-ary tree (fanout 16): test bench_weighted_shuffle_new ... bench: 36,244 ns/iter (+/- 243) test bench_weighted_shuffle_shuffle ... bench: 149,082 ns/iter (+/- 1,474) Binary tree: test bench_weighted_shuffle_new ... bench: 58,514 ns/iter (+/- 229) test bench_weighted_shuffle_shuffle ... bench: 269,961 ns/iter (+/- 16,446) Fenwick tree: test bench_weighted_shuffle_new ... bench: 39,413 ns/iter (+/- 179) test bench_weighted_shuffle_shuffle ... bench: 364,771 ns/iter (+/- 2,078) The improvements become even more significant as there are more items to shuffle. With 20_000 weights: N-ary tree (fanout 16): test bench_weighted_shuffle_new ... bench: 200,659 ns/iter (+/- 4,395) test bench_weighted_shuffle_shuffle ... bench: 941,928 ns/iter (+/- 26,492) Binary tree: test bench_weighted_shuffle_new ... bench: 881,114 ns/iter (+/- 12,343) test bench_weighted_shuffle_shuffle ... bench: 1,822,257 ns/iter (+/- 12,772) Fenwick tree: test bench_weighted_shuffle_new ... bench: 276,936 ns/iter (+/- 14,692) test bench_weighted_shuffle_shuffle ... bench: 2,644,713 ns/iter (+/- 49,252) (cherry picked from commit 30eecd6)
#429) implements weighted shuffle using N-ary tree (#259) This is port of firedancer's implementation of weighted shuffle: https://github.com/firedancer-io/firedancer/blob/3401bfc26/src/ballet/wsample/fd_wsample.c #185 implemented weighted shuffle using binary tree. Though asymptotically a binary tree has better performance, compared to a Fenwick tree, it has less cache locality resulting in smaller improvements and in particular slower WeightedShuffle::new. In order to improve cache locality and reduce the overheads of traversing the tree, this commit instead uses a generalized N-ary tree with fanout of 16, showing significant improvements in both WeightedShuffle::new and WeightedShuffle::shuffle. With 4000 weights: N-ary tree (fanout 16): test bench_weighted_shuffle_new ... bench: 36,244 ns/iter (+/- 243) test bench_weighted_shuffle_shuffle ... bench: 149,082 ns/iter (+/- 1,474) Binary tree: test bench_weighted_shuffle_new ... bench: 58,514 ns/iter (+/- 229) test bench_weighted_shuffle_shuffle ... bench: 269,961 ns/iter (+/- 16,446) Fenwick tree: test bench_weighted_shuffle_new ... bench: 39,413 ns/iter (+/- 179) test bench_weighted_shuffle_shuffle ... bench: 364,771 ns/iter (+/- 2,078) The improvements become even more significant as there are more items to shuffle. With 20_000 weights: N-ary tree (fanout 16): test bench_weighted_shuffle_new ... bench: 200,659 ns/iter (+/- 4,395) test bench_weighted_shuffle_shuffle ... bench: 941,928 ns/iter (+/- 26,492) Binary tree: test bench_weighted_shuffle_new ... bench: 881,114 ns/iter (+/- 12,343) test bench_weighted_shuffle_shuffle ... bench: 1,822,257 ns/iter (+/- 12,772) Fenwick tree: test bench_weighted_shuffle_new ... bench: 276,936 ns/iter (+/- 14,692) test bench_weighted_shuffle_shuffle ... bench: 2,644,713 ns/iter (+/- 49,252) (cherry picked from commit 30eecd6) Co-authored-by: behzad nouri <[email protected]>
…-xyz#259) (anza-xyz#429) implements weighted shuffle using N-ary tree (anza-xyz#259) This is port of firedancer's implementation of weighted shuffle: https://github.com/firedancer-io/firedancer/blob/3401bfc26/src/ballet/wsample/fd_wsample.c anza-xyz#185 implemented weighted shuffle using binary tree. Though asymptotically a binary tree has better performance, compared to a Fenwick tree, it has less cache locality resulting in smaller improvements and in particular slower WeightedShuffle::new. In order to improve cache locality and reduce the overheads of traversing the tree, this commit instead uses a generalized N-ary tree with fanout of 16, showing significant improvements in both WeightedShuffle::new and WeightedShuffle::shuffle. With 4000 weights: N-ary tree (fanout 16): test bench_weighted_shuffle_new ... bench: 36,244 ns/iter (+/- 243) test bench_weighted_shuffle_shuffle ... bench: 149,082 ns/iter (+/- 1,474) Binary tree: test bench_weighted_shuffle_new ... bench: 58,514 ns/iter (+/- 229) test bench_weighted_shuffle_shuffle ... bench: 269,961 ns/iter (+/- 16,446) Fenwick tree: test bench_weighted_shuffle_new ... bench: 39,413 ns/iter (+/- 179) test bench_weighted_shuffle_shuffle ... bench: 364,771 ns/iter (+/- 2,078) The improvements become even more significant as there are more items to shuffle. With 20_000 weights: N-ary tree (fanout 16): test bench_weighted_shuffle_new ... bench: 200,659 ns/iter (+/- 4,395) test bench_weighted_shuffle_shuffle ... bench: 941,928 ns/iter (+/- 26,492) Binary tree: test bench_weighted_shuffle_new ... bench: 881,114 ns/iter (+/- 12,343) test bench_weighted_shuffle_shuffle ... bench: 1,822,257 ns/iter (+/- 12,772) Fenwick tree: test bench_weighted_shuffle_new ... bench: 276,936 ns/iter (+/- 14,692) test bench_weighted_shuffle_shuffle ... bench: 2,644,713 ns/iter (+/- 49,252) (cherry picked from commit 30eecd6) Co-authored-by: behzad nouri <[email protected]>
This is port of firedancer's implementation of weighted shuffle:
https://github.com/firedancer-io/firedancer/blob/3401bfc26/src/ballet/wsample/fd_wsample.c
Problem
#185 implemented weighted shuffle using binary tree. Though asymptotically a
binary tree has better performance, compared to a Fenwick tree, it is
less cache local resulting in smaller improvements and in particular
slower
WeightedShuffle::new
.Summary of Changes
In order to improve cache locality and reduce the overheads of
traversing the tree, this commit instead uses a generalized N-ary tree
with fanout of 16, showing significant improvements in both
WeightedShuffle::new
andWeightedShuffle::shuffle
.With 4000 weights:
N-ary tree (fanout 16):
Binary tree:
Fenwick tree:
The improvements become even more significant as there are more items to
shuffle. With 20_000 weights:
N-ary tree (fanout 16):
Binary tree:
Fenwick tree: