RFR: 8322768: Optimize non-subword vector compress and expand APIs for AVX2 target. [v2]
Emanuel Peter
epeter at openjdk.org
Tue Jan 9 14:16:27 UTC 2024
On Tue, 9 Jan 2024 06:13:44 GMT, Jatin Bhateja <jbhateja at openjdk.org> wrote:
>> Yes, IF it is vectorized, then there is no difference between high and low density. My concern was more if vectorization is preferrable over the scalar alternative in the low-density case, where branch prediction is more stable.
>
> At runtime we do need to scan entire mask to pick the compressible lane corresponding to set mask bit. Thus the loop overhead of mask compare (BTW masks are held in a vector register for AVX2 targets) and jump will anyways be incurred , in addition for sparsely populated mask we may incur additional misprediction penalty for not taking if block which extracts an element from appropriate source vector lane and insert into destination vector lane. Overall vector solution will win for most common cases for varying mask and also for very sparsely populate masks. Here is the result of setting just a single mask bit.
>
>
> @Benchmark
> public void fuzzyFilterIntColumn() {
> int i = 0;
> int j = 0;
> long maskctr = 1;
> int endIndex = ispecies.loopBound(size);
> for (; i < endIndex; i += ispecies.length()) {
> IntVector vec = IntVector.fromArray(ispecies, intinCol, i);
> VectorMask<Integer> pred = VectorMask.fromLong(ispecies, 1);
> vec.compress(pred).intoArray(intoutCol, j);
> j += pred.trueCount();
> }
> }
>
>
> Baseline:
> Benchmark (size) Mode Cnt Score Error Units
> ColumnFilterBenchmark.fuzzyFilterIntColumn 1024 thrpt 2 379.059 ops/ms
> ColumnFilterBenchmark.fuzzyFilterIntColumn 2047 thrpt 2 188.355 ops/ms
> ColumnFilterBenchmark.fuzzyFilterIntColumn 4096 thrpt 2 95.315 ops/ms
>
>
> Withopt:
> Benchmark (size) Mode Cnt Score Error Units
> ColumnFilterBenchmark.fuzzyFilterIntColumn 1024 thrpt 2 7390.074 ops/ms
> ColumnFilterBenchmark.fuzzyFilterIntColumn 2047 thrpt 2 3483.247 ops/ms
> ColumnFilterBenchmark.fuzzyFilterIntColumn 4096 thrpt 2 1823.817 ops/ms
Nice, thanks for the data!
-------------
PR Review Comment: https://git.openjdk.org/jdk/pull/17261#discussion_r1446138902
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