Package org.apache.lucene.util

Class VectorUtil

  • public final class VectorUtil
extends Object
    Utilities for computations with numeric arrays, especially algebraic operations like vector dot products. This class uses SIMD vectorization if the corresponding Java module is available and enabled. To enable vectorized code, pass --add-modules jdk.incubator.vector to Java's command line.

    It will use CPU's FMA instructions if it is known to perform faster than separate multiply+add. This requires at least Hotspot C2 enabled, which is the default for OpenJDK based JVMs.

    To explicitly disable or enable FMA usage, pass the following system properties:

    • -Dlucene.useScalarFMA=(auto|true|false) for scalar operations
    • -Dlucene.useVectorFMA=(auto|true|false) for vectorized operations (with vector incubator module)

    The default is auto, which enables this for known CPU types and JVM settings. If Hotspot C2 is disabled, FMA and vectorization are not used.

    Vectorization and FMA is only supported for Hotspot-based JVMs; it won't work on OpenJ9-based JVMs unless they provide HotSpotDiagnosticMXBean. Please also make sure that you have the jdk.management module enabled in modularized applications.

    • Method Summary

      All Methods Static Methods Concrete Methods 
      Modifier and Type Method Description
      static void add​(float[] u, float[] v)
      Adds the second argument to the first
      static float[] checkFinite​(float[] v)
      Checks if a float vector only has finite components.
      static float cosine​(byte[] a, byte[] b)
      Returns the cosine similarity between the two vectors.
      static float cosine​(float[] a, float[] b)
      Returns the cosine similarity between the two vectors.
      static int dotProduct​(byte[] a, byte[] b)
      Dot product computed over signed bytes.
      static float dotProduct​(float[] a, float[] b)
      Returns the vector dot product of the two vectors.
      static float dotProductScore​(byte[] a, byte[] b)
      Dot product score computed over signed bytes, scaled to be in [0, 1].
      static int int4DotProduct​(byte[] a, byte[] b)  
      static int int4DotProductPacked​(byte[] unpacked, byte[] packed)
      Dot product computed over int4 (values between [0,15]) bytes.
      static float[] l2normalize​(float[] v)
      Modifies the argument to be unit length, dividing by its l2-norm.
      static float[] l2normalize​(float[] v, boolean throwOnZero)
      Modifies the argument to be unit length, dividing by its l2-norm.
      static float scaleMaxInnerProductScore​(float vectorDotProductSimilarity)  
      static int squareDistance​(byte[] a, byte[] b)
      Returns the sum of squared differences of the two vectors.
      static float squareDistance​(float[] a, float[] b)
      Returns the sum of squared differences of the two vectors.
      static int xorBitCount​(byte[] a, byte[] b)
      XOR bit count computed over signed bytes.

    • Method Detail

      • dotProduct

        public static float dotProduct​(float[] a,
                               float[] b)
        Returns the vector dot product of the two vectors.
        Throws:
        IllegalArgumentException - if the vectors' dimensions differ.

      • cosine

        public static float cosine​(float[] a,
                           float[] b)
        Returns the cosine similarity between the two vectors.
        Throws:
        IllegalArgumentException - if the vectors' dimensions differ.

      • cosine

        public static float cosine​(byte[] a,
                           byte[] b)
        Returns the cosine similarity between the two vectors.

      • squareDistance

        public static float squareDistance​(float[] a,
                                   float[] b)
        Returns the sum of squared differences of the two vectors.
        Throws:
        IllegalArgumentException - if the vectors' dimensions differ.

      • squareDistance

        public static int squareDistance​(byte[] a,
                                 byte[] b)
        Returns the sum of squared differences of the two vectors.

      • l2normalize

        public static float[] l2normalize​(float[] v)
        Modifies the argument to be unit length, dividing by its l2-norm. IllegalArgumentException is thrown for zero vectors.
        Returns:
        the input array after normalization

      • l2normalize

        public static float[] l2normalize​(float[] v,
                                  boolean throwOnZero)
        Modifies the argument to be unit length, dividing by its l2-norm.
        Parameters:
        v - the vector to normalize
        throwOnZero - whether to throw an exception when v has all zeros
        Returns:
        the input array after normalization
        Throws:
        IllegalArgumentException - when the vector is all zero and throwOnZero is true

      • add

        public static void add​(float[] u,
                       float[] v)
        Adds the second argument to the first
        Parameters:
        u - the destination
        v - the vector to add to the destination

      • dotProduct

        public static int dotProduct​(byte[] a,
                             byte[] b)
        Dot product computed over signed bytes.
        Parameters:
        a - bytes containing a vector
        b - bytes containing another vector, of the same dimension
        Returns:
        the value of the dot product of the two vectors

      • int4DotProduct

        public static int int4DotProduct​(byte[] a,
                                 byte[] b)

      • int4DotProductPacked

        public static int int4DotProductPacked​(byte[] unpacked,
                                       byte[] packed)
        Dot product computed over int4 (values between [0,15]) bytes. The second vector is considered "packed" (i.e. every byte representing two values). The following packing is assumed: 
           packed[0] = (raw[0] * 16) | raw[packed.length];
   packed[1] = (raw[1] * 16) | raw[packed.length + 1];
   ...
   packed[packed.length - 1] = (raw[packed.length - 1] * 16) | raw[2 * packed.length - 1];
        Parameters:
        unpacked - the unpacked vector, of even length
        packed - the packed vector, of length (unpacked.length + 1) / 2
        Returns:
        the value of the dot product of the two vectors

      • xorBitCount

        public static int xorBitCount​(byte[] a,
                              byte[] b)
        XOR bit count computed over signed bytes.
        Parameters:
        a - bytes containing a vector
        b - bytes containing another vector, of the same dimension
        Returns:
        the value of the XOR bit count of the two vectors

      • dotProductScore

        public static float dotProductScore​(byte[] a,
                                    byte[] b)
        Dot product score computed over signed bytes, scaled to be in [0, 1].
        Parameters:
        a - bytes containing a vector
        b - bytes containing another vector, of the same dimension
        Returns:
        the value of the similarity function applied to the two vectors

      • scaleMaxInnerProductScore

        public static float scaleMaxInnerProductScore​(float vectorDotProductSimilarity)
        Parameters:
        vectorDotProductSimilarity - the raw similarity between two vectors
        Returns:
        A scaled score preventing negative scores for maximum-inner-product

      • checkFinite

        public static float[] checkFinite​(float[] v)
        Checks if a float vector only has finite components.
        Parameters:
        v - bytes containing a vector
        Returns:
        the vector for call-chaining
        Throws:
        IllegalArgumentException - if any component of vector is not finite