Adds new unexposed and experimental IVF format (elastic#127528)

Author: benwtrent

benchmarks/src/main/java/org/elasticsearch/benchmark/vector/OSQScorerBenchmark.java

@@ -17,7 +17,7 @@
 import org.apache.lucene.util.VectorUtil;
 import org.apache.lucene.util.quantization.OptimizedScalarQuantizer;
 import org.elasticsearch.common.logging.LogConfigurator;
-import org.elasticsearch.simdvec.internal.vectorization.ES91OSQVectorsScorer;
+import org.elasticsearch.simdvec.ES91OSQVectorsScorer;
 import org.elasticsearch.simdvec.internal.vectorization.ESVectorizationProvider;
 import org.openjdk.jmh.annotations.Benchmark;
 import org.openjdk.jmh.annotations.BenchmarkMode;

libs/simdvec/src/main/java/org/elasticsearch/simdvec/internal/vectorization/ES91OSQVectorsScorer.java renamed to libs/simdvec/src/main/java/org/elasticsearch/simdvec/ES91OSQVectorsScorer.java

@@ -6,7 +6,7 @@
  * your election, the "Elastic License 2.0", the "GNU Affero General Public
  * License v3.0 only", or the "Server Side Public License, v 1".
  */
-package org.elasticsearch.simdvec.internal.vectorization;
+package org.elasticsearch.simdvec;
 
 import org.apache.lucene.index.VectorSimilarityFunction;
 import org.apache.lucene.store.IndexInput;

libs/simdvec/src/main/java/org/elasticsearch/simdvec/ESVectorUtil.java

@@ -9,11 +9,13 @@
 
 package org.elasticsearch.simdvec;
 
+import org.apache.lucene.store.IndexInput;
 import org.apache.lucene.util.BitUtil;
 import org.apache.lucene.util.Constants;
 import org.elasticsearch.simdvec.internal.vectorization.ESVectorUtilSupport;
 import org.elasticsearch.simdvec.internal.vectorization.ESVectorizationProvider;
 
+import java.io.IOException;
 import java.lang.invoke.MethodHandle;
 import java.lang.invoke.MethodHandles;
 import java.lang.invoke.MethodType;
@@ -41,6 +43,10 @@ public class ESVectorUtil {
 
     private static final ESVectorUtilSupport IMPL = ESVectorizationProvider.getInstance().getVectorUtilSupport();
 
+    public static ES91OSQVectorsScorer getES91OSQVectorsScorer(IndexInput input, int dimension) throws IOException {
+        return ESVectorizationProvider.getInstance().newES91OSQVectorsScorer(input, dimension);
+    }
+
     public static long ipByteBinByte(byte[] q, byte[] d) {
         if (q.length != d.length * B_QUERY) {
             throw new IllegalArgumentException("vector dimensions incompatible: " + q.length + "!= " + B_QUERY + " x " + d.length);
@@ -211,4 +217,40 @@ public static void centerAndCalculateOSQStatsDp(float[] target, float[] centroid
         assert stats.length == 6;
         IMPL.centerAndCalculateOSQStatsDp(target, centroid, centered, stats);
     }
+
+    /**
+     * Calculates the difference between two vectors and stores the result in a third vector.
+     * @param v1 the first vector
+     * @param v2 the second vector
+     * @param result the result vector, must be the same length as the input vectors
+     */
+    public static void subtract(float[] v1, float[] v2, float[] result) {
+        if (v1.length != v2.length) {
+            throw new IllegalArgumentException("vector dimensions differ: " + v1.length + "!=" + v2.length);
+        }
+        if (result.length != v1.length) {
+            throw new IllegalArgumentException("vector dimensions differ: " + result.length + "!=" + v1.length);
+        }
+        for (int i = 0; i < v1.length; i++) {
+            result[i] = v1[i] - v2[i];
+        }
+    }
+
+    /**
+     * calculates the spill-over score for a vector and a centroid, given its residual with
+     * its actually nearest centroid
+     * @param v1 the vector
+     * @param centroid the centroid
+     * @param originalResidual the residual with the actually nearest centroid
+     * @return the spill-over score (soar)
+     */
+    public static float soarResidual(float[] v1, float[] centroid, float[] originalResidual) {
+        if (v1.length != centroid.length) {
+            throw new IllegalArgumentException("vector dimensions differ: " + v1.length + "!=" + centroid.length);
+        }
+        if (originalResidual.length != v1.length) {
+            throw new IllegalArgumentException("vector dimensions differ: " + originalResidual.length + "!=" + v1.length);
+        }
+        return IMPL.soarResidual(v1, centroid, originalResidual);
+    }
 }

libs/simdvec/src/main/java/org/elasticsearch/simdvec/internal/vectorization/DefaultESVectorUtilSupport.java

@@ -138,6 +138,18 @@ public void centerAndCalculateOSQStatsDp(float[] target, float[] centroid, float
         stats[5] = centroidDot;
     }
 
+    @Override
+    public float soarResidual(float[] v1, float[] centroid, float[] originalResidual) {
+        assert v1.length == centroid.length;
+        assert v1.length == originalResidual.length;
+        float proj = 0;
+        for (int i = 0; i < v1.length; i++) {
+            float djk = v1[i] - centroid[i];
+            proj = fma(djk, originalResidual[i], proj);
+        }
+        return proj;
+    }
+
     public static int ipByteBitImpl(byte[] q, byte[] d) {
         return ipByteBitImpl(q, d, 0);
     }

libs/simdvec/src/main/java/org/elasticsearch/simdvec/internal/vectorization/DefaultESVectorizationProvider.java

@@ -10,6 +10,7 @@
 package org.elasticsearch.simdvec.internal.vectorization;
 
 import org.apache.lucene.store.IndexInput;
+import org.elasticsearch.simdvec.ES91OSQVectorsScorer;
 
 import java.io.IOException;
 

libs/simdvec/src/main/java/org/elasticsearch/simdvec/internal/vectorization/ESVectorUtilSupport.java

@@ -28,4 +28,7 @@ public interface ESVectorUtilSupport {
     void centerAndCalculateOSQStatsEuclidean(float[] target, float[] centroid, float[] centered, float[] stats);
 
     void centerAndCalculateOSQStatsDp(float[] target, float[] centroid, float[] centered, float[] stats);
+
+    float soarResidual(float[] v1, float[] centroid, float[] originalResidual);
+
 }

libs/simdvec/src/main/java/org/elasticsearch/simdvec/internal/vectorization/ESVectorizationProvider.java

@@ -10,6 +10,7 @@
 package org.elasticsearch.simdvec.internal.vectorization;
 
 import org.apache.lucene.store.IndexInput;
+import org.elasticsearch.simdvec.ES91OSQVectorsScorer;
 
 import java.io.IOException;
 import java.util.Objects;

libs/simdvec/src/main21/java/org/elasticsearch/simdvec/internal/vectorization/ESVectorizationProvider.java

@@ -13,6 +13,7 @@
 import org.apache.lucene.util.Constants;
 import org.elasticsearch.logging.LogManager;
 import org.elasticsearch.logging.Logger;
+import org.elasticsearch.simdvec.ES91OSQVectorsScorer;
 
 import java.io.IOException;
 import java.util.Locale;

libs/simdvec/src/main21/java/org/elasticsearch/simdvec/internal/vectorization/MemorySegmentES91OSQVectorsScorer.java

@@ -20,6 +20,7 @@
 import org.apache.lucene.store.IndexInput;
 import org.apache.lucene.util.VectorUtil;
 import org.apache.lucene.util.quantization.OptimizedScalarQuantizer;
+import org.elasticsearch.simdvec.ES91OSQVectorsScorer;
 
 import java.io.IOException;
 import java.lang.foreign.MemorySegment;

libs/simdvec/src/main21/java/org/elasticsearch/simdvec/internal/vectorization/PanamaESVectorUtilSupport.java

@@ -367,6 +367,49 @@ public float calculateOSQLoss(float[] target, float[] interval, float step, floa
         return (1f - lambda) * xe * xe / norm2 + lambda * e;
     }
 
+    @Override
+    public float soarResidual(float[] v1, float[] centroid, float[] originalResidual) {
+        assert v1.length == centroid.length;
+        assert v1.length == originalResidual.length;
+        float proj = 0;
+        int i = 0;
+        if (v1.length > 2 * FLOAT_SPECIES.length()) {
+            FloatVector projVec1 = FloatVector.zero(FLOAT_SPECIES);
+            FloatVector projVec2 = FloatVector.zero(FLOAT_SPECIES);
+            int unrolledLimit = FLOAT_SPECIES.loopBound(v1.length) - FLOAT_SPECIES.length();
+            for (; i < unrolledLimit; i += 2 * FLOAT_SPECIES.length()) {
+                // one
+                FloatVector v1Vec0 = FloatVector.fromArray(FLOAT_SPECIES, v1, i);
+                FloatVector centroidVec0 = FloatVector.fromArray(FLOAT_SPECIES, centroid, i);
+                FloatVector originalResidualVec0 = FloatVector.fromArray(FLOAT_SPECIES, originalResidual, i);
+                FloatVector djkVec0 = v1Vec0.sub(centroidVec0);
+                projVec1 = fma(djkVec0, originalResidualVec0, projVec1);
+
+                // two
+                FloatVector v1Vec1 = FloatVector.fromArray(FLOAT_SPECIES, v1, i + FLOAT_SPECIES.length());
+                FloatVector centroidVec1 = FloatVector.fromArray(FLOAT_SPECIES, centroid, i + FLOAT_SPECIES.length());
+                FloatVector originalResidualVec1 = FloatVector.fromArray(FLOAT_SPECIES, originalResidual, i + FLOAT_SPECIES.length());
+                FloatVector djkVec1 = v1Vec1.sub(centroidVec1);
+                projVec2 = fma(djkVec1, originalResidualVec1, projVec2);
+            }
+            // vector tail
+            for (; i < FLOAT_SPECIES.loopBound(v1.length); i += FLOAT_SPECIES.length()) {
+                FloatVector v1Vec = FloatVector.fromArray(FLOAT_SPECIES, v1, i);
+                FloatVector centroidVec = FloatVector.fromArray(FLOAT_SPECIES, centroid, i);
+                FloatVector originalResidualVec = FloatVector.fromArray(FLOAT_SPECIES, originalResidual, i);
+                FloatVector djkVec = v1Vec.sub(centroidVec);
+                projVec1 = fma(djkVec, originalResidualVec, projVec1);
+            }
+            proj += projVec1.add(projVec2).reduceLanes(ADD);
+        }
+        // tail
+        for (; i < v1.length; i++) {
+            float djk = v1[i] - centroid[i];
+            proj = fma(djk, originalResidual[i], proj);
+        }
+        return proj;
+    }
+
     private static final VectorSpecies<Byte> BYTE_SPECIES_128 = ByteVector.SPECIES_128;
     private static final VectorSpecies<Byte> BYTE_SPECIES_256 = ByteVector.SPECIES_256;