Bulk score hnsw diversity check

lucene/CHANGES.txt

@@ -330,6 +330,9 @@ Optimizations
 
 * GITHUB#15585: Added shared prefetch counter to maintain count across clones and slices of MemorySegmentIndexInput. (Shubham Sharma)
 
+* GITHUB#15607: Utilize bulk scoring for diversity checking when building HNSW vector indices. This results
+  in some performance improvements during indexing and segment merges. (Ben Trent)
+
 Bug Fixes
 ---------------------
 * GITHUB#14161: PointInSetQuery's constructor now throws IllegalArgumentException

lucene/core/src/java/org/apache/lucene/util/hnsw/HnswGraphBuilder.java

@@ -64,9 +64,13 @@ public class HnswGraphBuilder implements HnswBuilder {
   @SuppressWarnings("NonFinalStaticField")
   public static long randSeed = DEFAULT_RAND_SEED;
 
+  private static final int MAX_BULK_SCORE_NODES = 8;
+
   protected final int M; // max number of connections on upper layers
   private final double ml;
 
+  private final int[] bulkScoreNodes; // for bulk scoring
+  private final float[] bulkScores; // for bulk scoring
   private final SplittableRandom random;
   protected final UpdateableRandomVectorScorer scorer;
   protected final HnswGraphSearcher graphSearcher;
@@ -156,6 +160,10 @@ protected HnswGraphBuilder(
     this.hnsw = hnsw;
     this.hnswLock = hnswLock;
     this.graphSearcher = graphSearcher;
+    // pick a number that keeps us from scoring TOO much for diversity checking
+    // but enough to take advantage of bulk scoring
+    this.bulkScoreNodes = new int[MAX_BULK_SCORE_NODES];
+    this.bulkScores = new float[MAX_BULK_SCORE_NODES];
     entryCandidates = new GraphBuilderKnnCollector(1);
     beamCandidates = new GraphBuilderKnnCollector(beamWidth);
     beamCandidates0 = new GraphBuilderKnnCollector(Math.min(beamWidth / 2, M * 3));
@@ -470,9 +478,11 @@ static void popToScratch(GraphBuilderKnnCollector candidates, NeighborArray scra
    */
   private boolean diversityCheck(float score, NeighborArray neighbors, RandomVectorScorer scorer)
       throws IOException {
-    for (int i = 0; i < neighbors.size(); i++) {
-      float neighborSimilarity = scorer.score(neighbors.nodes()[i]);
-      if (neighborSimilarity >= score) {
+    final int bulkScoreChunk = Math.min((neighbors.size() + 1) / 2, bulkScoreNodes.length);
+    for (int scored = 0; scored < neighbors.size(); scored += bulkScoreChunk) {
+      int chunkSize = Math.min(bulkScoreChunk, neighbors.size() - scored);
+      System.arraycopy(neighbors.nodes(), scored, bulkScoreNodes, 0, chunkSize);
+      if (scorer.bulkScore(bulkScoreNodes, bulkScores, chunkSize) >= score) {
         return false;
       }
     }