rmuir opened a new pull request, #12747:
URL: https://github.com/apache/lucene/pull/12747

   This benchmark is too noisy across forks which makes comparisons impossible 
and misleading. Especially vectorized float methods on some machines: it is 
almost useless.
   
   I spent some time to reduce the noise, unfortunately it results in the 
benchmark being 2x slower. We can do tricky jvm args but what is best is to 
just do many forks. 
   
   I now see reasonably stable results on Graviton3E with 256-bit ARM SVE (!) 
and look forward to actually investigating this thing more than just 
stabilizing this benchmark :)
   ```
   Benchmark                                   (size)   Mode  Cnt   Score    
Error   Units
   VectorUtilBenchmark.binaryCosineScalar        1024  thrpt   15   0.842 ±  
0.001  ops/us
   VectorUtilBenchmark.binaryCosineVector        1024  thrpt   15   4.811 ±  
0.006  ops/us
   VectorUtilBenchmark.binaryDotProductScalar    1024  thrpt   15   2.370 ±  
0.001  ops/us
   VectorUtilBenchmark.binaryDotProductVector    1024  thrpt   15   8.037 ±  
0.001  ops/us
   VectorUtilBenchmark.binarySquareScalar        1024  thrpt   15   2.450 ±  
0.034  ops/us
   VectorUtilBenchmark.binarySquareVector        1024  thrpt   15   6.703 ±  
0.010  ops/us
   VectorUtilBenchmark.floatCosineScalar         1024  thrpt   15   0.682 ±  
0.001  ops/us
   VectorUtilBenchmark.floatCosineVector         1024  thrpt   75   5.498 ±  
0.004  ops/us
   VectorUtilBenchmark.floatDotProductScalar     1024  thrpt   15   2.409 ±  
0.013  ops/us
   VectorUtilBenchmark.floatDotProductVector     1024  thrpt   75  12.446 ±  
0.343  ops/us
   VectorUtilBenchmark.floatSquareScalar         1024  thrpt   15   2.172 ±  
0.007  ops/us
   VectorUtilBenchmark.floatSquareVector         1024  thrpt   75  11.655 ±  
0.152  ops/us
   ```


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