ML-dev-crypto commented on issue #15606:
URL: https://github.com/apache/lucene/issues/15606#issuecomment-3849130759

   Hi maintainers
   
   PLEASE ASSIGN THUS ISSUE TO ME 
   
   
   
   I’d like to take this issue and work on expanding bulk scoring usage in the 
remaining places where we still rely on single-vector scoring.
   
   From reviewing the code and the discussion here, I see several clear 
candidates where RandomVectorScorer.score() / VectorScorer.score() are still 
used and could benefit from the bulk scorer API:
   
   Areas I plan to focus on
   
   HNSW graph construction
   
   HnswGraphBuilder#diversityCheck
   This looks like a strong candidate for bulk scoring during diversity checks, 
and I’m currently reviewing this path in detail.
   
   NeighborArray#isWorstNonDiverse
   Could potentially batch vector comparisons instead of scoring one-by-one.
   
   Higher-level vector scorers
   
   DiversifyingChildrenVectorScorer#nextParent
   Investigate bulk-scoring children vectors rather than individual scoring 
calls.
   
   VectorSimilarityScorerSupplier
   Explore whether it can implement or delegate to BulkScorer when available.
   
   Value sources
   
   FullPrecisionFloatVectorSimilarityValuesSource
   
   VectorSimilarityValuesSource
   These currently expose DoubleValues, which lacks bulk interfaces, but there 
may be opportunities to extend or adapt these paths to support bulk scoring 
where possible.
   
   Direct VectorUtil usage
   
   KMeans
   
   BpVectorReorderer
   These may be harder to refactor, but I’ll evaluate whether limited bulk 
scoring can still be applied safely.
   
   Goal
   
   The goal would be to:
   
   Reduce remaining single-vector scoring hot paths
   
   Improve consistency of bulk scoring usage across ANN and higher-level search 
flows
   
   Deliver measurable performance improvements without changing scoring 
semantics
   
   Thanks!


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