kaivalnp commented on PR #15285:
URL: https://github.com/apache/lucene/pull/15285#issuecomment-3398444020

   > It's hard for human eyes + brain to scan all those numbers and confirm 
there's no real difference
   
   Haha true :)
   I fed the raw data to an LLM and asked it to report percentage differences:
   
   | Benchmark | Baseline Score (ops/μs) | Candidate Score (ops/μs) | % 
Difference |
   
|-----------|------------------------|-------------------------|--------------|
   | floatCosineVector | 8.913 | 8.646 | -3.00% |
   | floatDotProductVector | 12.561 | 12.249 | -2.48% |
   | binaryHalfByteDotProductBothPackedVector | 11.652 | 11.498 | -1.32% |
   | l2NormalizeVector | 12.349 | 12.207 | -1.15% |
   | binaryDotProductUint8Scalar | 2.307 | 2.288 | -0.82% |
   | binarySquareScalar | 2.431 | 2.413 | -0.74% |
   | binaryHalfByteSquareBothPackedVector | 12.614 | 12.562 | -0.41% |
   | floatSquareScalar | 3.181 | 3.171 | -0.31% |
   | floatCosineScalar | 1.419 | 1.415 | -0.28% |
   | binaryHalfByteSquareVector | 18.526 | 18.487 | -0.21% |
   | binaryHalfByteDotProductScalar | 2.378 | 2.376 | -0.08% |
   | binarySquareUint8Scalar | 2.422 | 2.420 | -0.08% |
   | binaryHalfByteSquareSinglePackedScalar | 2.022 | 2.021 | -0.05% |
   | floatDotProductScalar | 3.734 | 3.733 | -0.03% |
   | binaryDotProductVector | 8.040 | 8.039 | -0.01% |
   | binarySquareVector | 6.710 | 6.709 | -0.01% |
   | binaryCosineScalar | 0.841 | 0.841 | 0.00% |
   | binaryDotProductUint8Vector | 8.040 | 8.040 | 0.00% |
   | binaryHalfByteDotProductSinglePackedVector | 2.627 | 2.627 | 0.00% |
   | binarySquareUint8Vector | 6.709 | 6.709 | 0.00% |
   | l2Normalize | 3.016 | 3.017 | 0.03% |
   | binaryHalfByteDotProductSinglePackedScalar | 2.446 | 2.449 | 0.12% |
   | binaryHalfByteDotProductBothPackedScalar | 2.368 | 2.376 | 0.34% |
   | binaryHalfByteSquareScalar | 2.465 | 2.474 | 0.36% |
   | binaryDotProductScalar | 2.289 | 2.298 | 0.39% |
   | binaryHalfByteDotProductVector | 20.677 | 20.785 | 0.52% |
   | binaryHalfByteSquareSinglePackedVector | 2.590 | 2.609 | 0.73% |
   | floatSquareVector | 12.370 | 12.483 | 0.91% |
   | binaryCosineVector | 4.778 | 4.860 | 1.72% |
   | binaryHalfByteSquareBothPackedScalar | 1.642 | 1.696 | 3.29% |
   
   Side note: I found this cool visualizer (https://jmh.morethan.io), which 
takes the JSON output of JMH (add `-rf json` to the command line), and can 
compare multiple runs too!
   
   For example, I re-ran a subset of functions and recorded their output in 
https://gist.github.com/kaivalnp/0424bd84326aebdecd10f8144fb46c73
   Now we can visualize the results at: 
https://jmh.morethan.io/?gist=0424bd84326aebdecd10f8144fb46c73
   
   Also found this GH action that automatically runs and compares JMH output: 
https://github.com/benchmark-action/github-action-benchmark, might be 
interesting to add to Lucene!


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