vsop-479 commented on PR #12846:
URL: https://github.com/apache/lucene/pull/12846#issuecomment-1842384044
> is this new approach helping cover more cases maybe?
Yes, Previous patch only apply copy for level 0 's acc in
``Lucene99SkipWriter.bufferSkip``, Current patch apply copy for all level's
acc in ``Lucene99SkipWriter.writeSkipData`` by adding a flag to indicates
wether this is an empty acc.
> when knowing when the accumulator is empty is the responsibility of the
caller rather than CompetitiveFreqNormAccumulator.
I will move the copy/addAll selection to caller.
Before that, there are some performance data I want to share:
First of all, I measured method execution time(without assertion):
Method | ns | diff
-- | -- | --
addAll | 48291 | -
copy | 17000 | +64.7%
And add the implementation to JMH to enable JIT's optimization(auto-unroll,
auto-vectorization):
````
Benchmark (size) Mode Cnt Score Error
Units
VectorUtilBenchmark.accAddAll 256 thrpt 15 17.311 ± 4.468
ops/us
VectorUtilBenchmark.accCopy 256 thrpt 15 21.417 ± 7.009
ops/us
Benchmark (size) Mode Cnt Score Error
Units
VectorUtilBenchmark.accAddAll 256 thrpt 15 19.943 ± 4.831
ops/us
VectorUtilBenchmark.accCopy 256 thrpt 15 16.516 ± 1.904
ops/us
````
The speedup is not stable, so I split the implementation into array part and
treeSet part.
1. Array part:
````
Benchmark (size) Mode Cnt Score Error
Units
VectorUtilBenchmark.arrayCopy 256 thrpt 15 141.356 ± 3.640
ops/us
VectorUtilBenchmark.arrayMax 256 thrpt 15 77.875 ± 1.310
ops/us
Benchmark (size) Mode Cnt Score Error
Units
VectorUtilBenchmark.arrayCopy 256 thrpt 15 138.484 ± 5.038
ops/us
VectorUtilBenchmark.arrayMax 256 thrpt 15 78.250 ± 0.992
ops/us
````
ArrayMax is the baseline that iterates the array and get the max value.
ArrayCopy uses ``System.arraycopy``, which get a explicit speedup.
2. TreeSet part:
````
Benchmark (size) Mode Cnt Score Error
Units
VectorUtilBenchmark.treeAddAll 256 thrpt 15 27.673 ± 19.096
ops/us
VectorUtilBenchmark.treeScalarAdd 256 thrpt 15 34.888 ± 14.321
ops/us
Benchmark (size) Mode Cnt Score Error
Units
VectorUtilBenchmark.treeAddAll 256 thrpt 15 25.342 ± 4.151
ops/us
VectorUtilBenchmark.treeScalarAdd 256 thrpt 15 42.673 ± 19.396
ops/us
````
I also measured the method performance without JMH:
Method | ns | diff
-- | -- | --
treeScalarAdd | 36000 | -
treeAddAll | 26875 | +25.3%
The method performance indicates that `TreeSet.addAll` get a better
performance, but JMH benchmark result indicates that scalarAdd(baseline) get a
better performance than `TreeSet.addAll`, which is unexpected for me. I am
still working on
finding out the reason.
Finally, I modified `acc.copy` to just copy the array but use the original
iterate add for treeSet, and measured the performance:
````
Benchmark (size) Mode Cnt Score Error
Units
VectorUtilBenchmark.accAddAll 256 thrpt 15 16.180 ± 3.014
ops/us
VectorUtilBenchmark.accCopy 256 thrpt 15 31.807 ± 12.811
ops/us
Benchmark (size) Mode Cnt Score Error
Units
VectorUtilBenchmark.accAddAll 256 thrpt 15 20.414 ± 3.693
ops/us
VectorUtilBenchmark.accCopy 256 thrpt 15 24.432 ± 6.862
ops/us
````
Now `acc.copy` get a speedup.
Any idea about that? @jpountz
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