Class RealSparseMatMult

java.lang.Object
org.flag4j.linalg.ops.sparse.coo.real.RealSparseMatMult
public final class RealSparseMatMult extends Object
This class contains low level implementations of matrix multiplication for real sparse matrices. WARNING: This class does not provide sanity checks.

  • Method Summary

    Modifier and Type
    Method
    Description
    static double[]
    concurrentStandard(double[] src1, int[] rowIndices1, int[] colIndices1, Shape shape1, double[] src2, int[] rowIndices2, int[] colIndices2, Shape shape2)
    Computes the matrix multiplication between two sparse matrices using a concurrent implementation of the standard algorithm.
    static double[]
    concurrentStandardVector(double[] src1, int[] rowIndices1, int[] colIndices1, Shape shape1, double[] src2, int[] indices)
    Computes the multiplication between a sparse matrix and a sparse vector using a concurrent implementation of the standard algorithm.
    static double[]
    standard(double[] src1, int[] rowIndices1, int[] colIndices1, Shape shape1, double[] src2, int[] rowIndices2, int[] colIndices2, Shape shape2)
    Computes the matrix multiplication between two sparse matrices using a standard algorithm.
    static double[]
    standardVector(double[] src1, int[] rowIndices1, int[] colIndices1, Shape shape1, double[] src2, int[] indices)
    Computes the multiplication between a sparse matrix and a sparse vector using a standard algorithm.

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

  • Method Details

    • standard

      public static double[] standard(double[] src1, int[] rowIndices1, int[] colIndices1, Shape shape1, double[] src2, int[] rowIndices2, int[] colIndices2, Shape shape2)
      Computes the matrix multiplication between two sparse matrices using a standard algorithm.
      Parameters:
      src1 - Non-zero data of the first sparse matrix.
      rowIndices1 - Row indices of non-zero data for the first sparse matrix.
      colIndices1 - Column indices of non-zero data for the first sparse matrix.
      shape1 - Shape of the first sparse matrix.
      src2 - Non-zero data of the second sparse matrix.
      rowIndices2 - Row indices of non-zero data for the second sparse matrix.
      colIndices2 - column indices of non-zero data for the second sparse matrix.
      shape2 - Shape of the second sparse matrix.
      Returns:
      The result of the matrix multiplication stored in a dense matrix.

    • concurrentStandard

      public static double[] concurrentStandard(double[] src1, int[] rowIndices1, int[] colIndices1, Shape shape1, double[] src2, int[] rowIndices2, int[] colIndices2, Shape shape2)
      Computes the matrix multiplication between two sparse matrices using a concurrent implementation of the standard algorithm.

      NOTE: Caution should be exercised when using this method. It is rarely faster than standard(double[], int[], int[], Shape, double[], int[], int[], Shape)
      Parameters:
      src1 - Non-zero data of the first sparse matrix.
      rowIndices1 - Row indices of non-zero data for the first sparse matrix.
      colIndices1 - Column indices of non-zero data for the first sparse matrix.
      shape1 - Shape of the first sparse matrix.
      src2 - Non-zero data of the second sparse matrix.
      rowIndices2 - Row indices of non-zero data for the second sparse matrix.
      colIndices2 - column indices of non-zero data for the second sparse matrix.
      shape2 - Shape of the second sparse matrix.
      Returns:
      The result of the matrix multiplication stored in a dense matrix.

    • standardVector

      public static double[] standardVector(double[] src1, int[] rowIndices1, int[] colIndices1, Shape shape1, double[] src2, int[] indices)
      Computes the multiplication between a sparse matrix and a sparse vector using a standard algorithm.
      Parameters:
      src1 - Non-zero data of the first sparse matrix.
      rowIndices1 - Row indices of non-zero data for the first sparse matrix.
      colIndices1 - Column indices of non-zero data for the first sparse matrix.
      shape1 - Shape of the first sparse matrix.
      src2 - Non-zero data of the second sparse matrix.
      indices - Indices of non-zero data in the sparse vector.
      Returns:
      The result of the matrix-vector multiplication stored in a dense matrix.

    • concurrentStandardVector

      public static double[] concurrentStandardVector(double[] src1, int[] rowIndices1, int[] colIndices1, Shape shape1, double[] src2, int[] indices)
      Computes the multiplication between a sparse matrix and a sparse vector using a concurrent implementation of the standard algorithm.
      Parameters:
      src1 - Non-zero data of the first sparse matrix.
      rowIndices1 - Row indices of non-zero data for the first sparse matrix.
      colIndices1 - Column indices of non-zero data for the first sparse matrix.
      shape1 - Shape of the first sparse matrix.
      src2 - Non-zero data of the second sparse matrix.
      indices - Indices of non-zero data in the sparse vector.
      Returns:
      The result of the matrix-vector multiplication stored in a dense matrix.