jegentile commented on PR #16200:
URL: https://github.com/apache/lucene/pull/16200#issuecomment-4623537667

   ## Benchmark Results
   
   Byte vector cosine scoring throughput (ops/μs, higher is better). Measured 
with JMH using `VectorScorerBenchmark` (3 forks, 4 warmup iterations, 5 
measurement iterations, padBytes=0).
   
   | Benchmark | Dim | Baseline (`main`) | This PR | Speedup |
   |---|---|---|---|---|
   | **Default (scalar)** | 128 | 6.35 ± 0.13 | 10.46 ± 0.23 | **+65%** |
   | **Default (scalar)** | 512 | 1.67 ± 0.05 | 3.01 ± 0.07 | **+81%** |
   | **Default (scalar)** | 1024 | 0.79 ± 0.02 | 1.55 ± 0.04 | **+95%** |
   | **MemSeg (Panama SIMD)** | 128 | 19.12 ± 0.41 | 24.31 ± 0.49 | **+27%** |
   | **MemSeg (Panama SIMD)** | 512 | 8.29 ± 0.58 | 10.74 ± 0.34 | **+30%** |
   | **MemSeg (Panama SIMD)** | 1024 | 4.63 ± 0.16 | 6.22 ± 0.20 | **+34%** |
   
   The scalar path improvement (~65-95%) comes from eliminating the query norm 
computation entirely from the loop. The SIMD path improvement (~27-34%) comes 
from removing one accumulator, one multiply, and one `reduceLanes` per vector 
iteration.
   
   **Environment:** OpenJDK 25.0.3, Linux 7.0.10-arch1-1


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