gf2121 commented on code in PR #14679:
URL: https://github.com/apache/lucene/pull/14679#discussion_r2093432298
##########
lucene/core/src/java/org/apache/lucene/search/similarities/Similarity.java:
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@@ -208,6 +208,25 @@ protected SimScorer() {}
*/
public abstract float score(float freq, long norm);
+ /**
+ * Batch-score documents. This method scores {@code size} documents at
once. The default
+ * implementation can be found below:
+ *
+ * <pre class="prettyprint">
+ * for (int i = 0; i < size; ++i) {
+ * scores[i] = score(freqs[i], norms[i]);
+ * }
+ * </pre>
+ *
+ * @see #score(float, long)
+ * @lucene.internal
+ */
+ public void score(int size, int[] freqs, long[] norms, float[] scores) {
+ for (int i = 0; i < size; ++i) {
+ scores[i] = score(freqs[i], norms[i]);
Review Comment:
> We may also be able to do a bit better than calling score in a loop
Yeah! I played with`BM25` a bit and the result looks promising:
```
Benchmark Mode Cnt Score Error Units
VectorizedBM25Benchmark.scoreBaseline thrpt 5 10.991 ± 0.356 ops/us
VectorizedBM25Benchmark.scoreVector thrpt 5 15.149 ± 0.029 ops/us
```
```
public static void scoreBaseline(int size, int[] freqs, long[] norms,
float[] scores, float[] cache, int weight, float[] buffer) {
for (int i = 0; i < size; ++i) {
float normInverse = cache[((byte) norms[i]) & 0xFF];
scores[i] = weight - weight / (1f + freqs[i] * normInverse);
}
}
public static void scoreVector(int size, int[] freqs, long[] norms, float[]
scores, float[] cache, int weight, float[] buffer) {
for (int i = 0; i < size; ++i) {
buffer[i] = cache[((byte) norms[i]) & 0xFF];
}
for (int i = 0; i < size; ++i) {
scores[i] = weight - weight / (1f + freqs[i] * buffer[i]);
}
}
```
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