Class LibMatrixMult


  • public class LibMatrixMult
    extends Object
    MB: Library for matrix multiplications including MM, MV, VV for all combinations of dense, sparse, ultrasparse representations and special operations such as transpose-self matrix multiplication.

    In general all implementations use internally dense outputs for direct access, but change the final result to sparse if necessary. The only exceptions are ultra-sparse matrix mult, wsloss and wsigmoid.

    • Method Detail

      • matrixMult

        public static MatrixBlock matrixMult​(MatrixBlock m1,
                                             MatrixBlock m2)
        Performs a matrix multiplication All variants use a IKJ access pattern, and internally use dense output. After the actual computation, we recompute nnz and check for sparse/dense representation.
        Parameters:
        m1 - first matrix
        m2 - second matrix
        Returns:
        ret Matrix Block
      • matrixMult

        public static MatrixBlock matrixMult​(MatrixBlock m1,
                                             MatrixBlock m2,
                                             int k)
        Performs a matrix multiplication All variants use a IKJ access pattern, and internally use dense output. After the actual computation, we recompute nnz and check for sparse/dense representation.
        Parameters:
        m1 - first matrix
        m2 - second matrix
        k - maximum parallelism
        Returns:
        ret Matrix Block
      • matrixMult

        public static MatrixBlock matrixMult​(MatrixBlock m1,
                                             MatrixBlock m2,
                                             MatrixBlock ret)
        Performs a matrix multiplication and stores the result in the output matrix. All variants use a IKJ access pattern, and internally use dense output. After the actual computation, we recompute nnz and check for sparse/dense representation.
        Parameters:
        m1 - first matrix
        m2 - second matrix
        ret - result matrix
        Returns:
        ret Matrix Block
      • matrixMult

        public static MatrixBlock matrixMult​(MatrixBlock m1,
                                             MatrixBlock m2,
                                             MatrixBlock ret,
                                             boolean fixedRet)
        This method allows one to disabling exam sparsity. This feature is useful if matrixMult is used as an intermediate operation (for example: LibMatrixDNN). It makes sense for LibMatrixDNN because the output is internally consumed by another dense instruction, which makes repeated conversion to sparse wasteful. This should be used in rare cases and if you are unsure, use the method 'matrixMult(MatrixBlock m1, MatrixBlock m2, MatrixBlock ret)' instead.
        Parameters:
        m1 - first matrix
        m2 - second matrix
        ret - result matrix
        fixedRet - if true, output representation is fixed and nnzs not recomputed
        Returns:
        ret Matrix Block
      • matrixMult

        public static MatrixBlock matrixMult​(MatrixBlock m1,
                                             MatrixBlock m2,
                                             MatrixBlock ret,
                                             int k)
        Performs a multi-threaded matrix multiplication and stores the result in the output matrix. The parameter k (k>=1) determines the max parallelism k' with k'=min(k, vcores, m1.rlen).
        Parameters:
        m1 - first matrix
        m2 - second matrix
        ret - result matrix
        k - maximum parallelism
        Returns:
        ret Matrix Block
      • matrixMult

        public static MatrixBlock matrixMult​(MatrixBlock m1,
                                             MatrixBlock m2,
                                             MatrixBlock ret,
                                             boolean fixedRet,
                                             int k)
        Performs a matrix multiplication and stores the result in the output matrix. All variants use a IKJ access pattern, and internally use dense output. After the actual computation, we recompute nnz and check for sparse/dense representation. This method allows one to disabling exam sparsity. This feature is useful if matrixMult is used as an intermediate operation (for example: LibMatrixDNN). It makes sense for LibMatrixDNN because the output is internally consumed by another dense instruction, which makes repeated conversion to sparse wasteful. This should be used in rare cases and if you are unsure, use the method 'matrixMult(MatrixBlock m1, MatrixBlock m2, MatrixBlock ret)' instead. The parameter k (k>=1) determines the max parallelism k' with k'=min(k, vcores, m1.rlen).
        Parameters:
        m1 - first matrix
        m2 - second matrix
        ret - result matrix
        fixedRet - if true, output representation is fixed and nnzs not recomputed
        k - maximum parallelism
        Returns:
        ret Matrix Block
      • matrixMultChain

        public static void matrixMultChain​(MatrixBlock mX,
                                           MatrixBlock mV,
                                           MatrixBlock mW,
                                           MatrixBlock ret,
                                           MapMultChain.ChainType ct)
        Performs a matrix multiplication chain operation of type t(X)%*%(X%*%v) or t(X)%*%(w*(X%*%v)). All variants use a IKJ access pattern, and internally use dense output. After the actual computation, we recompute nnz and check for sparse/dense representation.
        Parameters:
        mX - X matrix
        mV - v matrix
        mW - w matrix
        ret - result matrix
        ct - chain type
      • matrixMultChain

        public static void matrixMultChain​(MatrixBlock mX,
                                           MatrixBlock mV,
                                           MatrixBlock mW,
                                           MatrixBlock ret,
                                           MapMultChain.ChainType ct,
                                           int k)
        Performs a parallel matrix multiplication chain operation of type t(X)%*%(X%*%v) or t(X)%*%(w*(X%*%v)). The parameter k (k>=1) determines the max parallelism k' with k'=min(k, vcores, m1.rlen). NOTE: This multi-threaded mmchain operation has additional memory requirements of k*ncol(X)*8bytes for partial aggregation. Current max memory: 256KB; otherwise redirectly to sequential execution.
        Parameters:
        mX - X matrix
        mV - v matrix
        mW - w matrix
        ret - result matrix
        ct - chain type
        k - maximum parallelism
      • matrixMultTransposeSelf

        public static void matrixMultTransposeSelf​(MatrixBlock m1,
                                                   MatrixBlock ret,
                                                   boolean leftTranspose)
      • matrixMultTransposeSelf

        public static void matrixMultTransposeSelf​(MatrixBlock m1,
                                                   MatrixBlock ret,
                                                   boolean leftTranspose,
                                                   boolean copyToLowerTriangle)
      • matrixMultTransposeSelf

        public static void matrixMultTransposeSelf​(MatrixBlock m1,
                                                   MatrixBlock ret,
                                                   boolean leftTranspose,
                                                   int k)
        TSMM with optional transposed left side or not (Transposed self matrix multiplication)
        Parameters:
        m1 - The matrix to do tsmm
        ret - The output matrix to allocate the result to
        leftTranspose - If the left side should be considered transposed
        k - the number of threads to use
      • matrixMultWDivMM

        public static void matrixMultWDivMM​(MatrixBlock mW,
                                            MatrixBlock mU,
                                            MatrixBlock mV,
                                            MatrixBlock mX,
                                            MatrixBlock ret,
                                            WeightedDivMM.WDivMMType wt)
        NOTE: This operation has limited NaN support, which is acceptable because all our sparse-safe operations have only limited NaN support. If this is not intended behavior, please disable the rewrite. In detail, this operator will produce for W/(U%*%t(V)) a zero intermediate for each zero in W (even if UVij is zero which would give 0/0=NaN) but INF/-INF for non-zero entries in V where the corresponding cell in (Y%*%X) is zero.
        Parameters:
        mW - matrix W
        mU - matrix U
        mV - matrix V
        mX - matrix X
        ret - result type
        wt - weighted divide matrix multiplication type
      • matrixMultWDivMM

        public static void matrixMultWDivMM​(MatrixBlock mW,
                                            MatrixBlock mU,
                                            MatrixBlock mV,
                                            MatrixBlock mX,
                                            MatrixBlock ret,
                                            WeightedDivMM.WDivMMType wt,
                                            int k)
        NOTE: This operation has limited NaN support, which is acceptable because all our sparse-safe operations have only limited NaN support. If this is not intended behavior, please disable the rewrite. In detail, this operator will produce for W/(U%*%t(V)) a zero intermediate for each zero in W (even if UVij is zero which would give 0/0=NaN) but INF/-INF for non-zero entries in V where the corresponding cell in (Y%*%X) is zero.
        Parameters:
        mW - matrix W
        mU - matrix U
        mV - matrix V
        mX - matrix X
        ret - result matrix
        wt - weighted divide matrix multiplication type
        k - maximum parallelism
      • matrixMultDenseDenseMM

        public static void matrixMultDenseDenseMM​(DenseBlock a,
                                                  DenseBlock b,
                                                  DenseBlock c,
                                                  int n,
                                                  int cd,
                                                  int rl,
                                                  int ru,
                                                  int cl,
                                                  int cu)
      • dotProduct

        public static double dotProduct​(double[] a,
                                        double[] b,
                                        int ai,
                                        int bi,
                                        int len)
      • dotProduct

        public static double dotProduct​(double[] a,
                                        double[] b,
                                        int[] aix,
                                        int ai,
                                        int bi,
                                        int len)
      • vectMultiplyAdd

        public static void vectMultiplyAdd​(double aval,
                                           double[] b,
                                           double[] c,
                                           int bi,
                                           int ci,
                                           int len)
      • vectMultiplyAdd

        public static void vectMultiplyAdd​(double aval,
                                           double[] b,
                                           double[] c,
                                           int[] bix,
                                           int bi,
                                           int ci,
                                           int len)
      • vectMultiplyWrite

        public static void vectMultiplyWrite​(double aval,
                                             double[] b,
                                             double[] c,
                                             int bi,
                                             int ci,
                                             int len)
      • vectMultiplyInPlace

        public static void vectMultiplyInPlace​(double aval,
                                               double[] c,
                                               int ci,
                                               int len)
      • vectMultiplyWrite

        public static void vectMultiplyWrite​(double[] a,
                                             double[] b,
                                             double[] c,
                                             int ai,
                                             int bi,
                                             int ci,
                                             int len)
      • vectMultiplyWrite

        public static void vectMultiplyWrite​(double[] a,
                                             double[] b,
                                             double[] c,
                                             int[] bix,
                                             int ai,
                                             int bi,
                                             int ci,
                                             int len)
      • vectAdd

        public static void vectAdd​(double[] a,
                                   double bval,
                                   double[] c,
                                   int ai,
                                   int ci,
                                   int len)
      • vectAdd

        public static void vectAdd​(double[] a,
                                   double[] c,
                                   int ai,
                                   int ci,
                                   int len)
      • vectAdd

        public static void vectAdd​(double[] a,
                                   double[] c,
                                   int[] aix,
                                   int ai,
                                   int ci,
                                   int alen)
      • vectAddInPlace

        public static void vectAddInPlace​(double aval,
                                          double[] c,
                                          int ci,
                                          int len)
      • copyUpperToLowerTriangle

        public static long copyUpperToLowerTriangle​(MatrixBlock ret)
        Used for all version of TSMM where the result is known to be symmetric. Hence, we compute only the upper triangular matrix and copy this partial result down to lower triangular matrix once.
        Parameters:
        ret - matrix
        Returns:
        number of non zeros
      • prepMatrixMultTransposeSelfInput

        public static MatrixBlock prepMatrixMultTransposeSelfInput​(MatrixBlock m1,
                                                                   boolean leftTranspose,
                                                                   boolean par)
      • isSkinnyRightHandSide

        public static boolean isSkinnyRightHandSide​(long m1rlen,
                                                    long m1clen,
                                                    long m2rlen,
                                                    long m2clen,
                                                    boolean inclCacheSize)
      • satisfiesMultiThreadingConstraints

        public static boolean satisfiesMultiThreadingConstraints​(MatrixBlock m1,
                                                                 int k)
      • satisfiesMultiThreadingConstraints

        public static boolean satisfiesMultiThreadingConstraints​(MatrixBlock m1,
                                                                 boolean checkMem,
                                                                 boolean checkFLOPs,
                                                                 long FPfactor,
                                                                 int k)
      • satisfiesMultiThreadingConstraints

        public static boolean satisfiesMultiThreadingConstraints​(MatrixBlock m1,
                                                                 MatrixBlock m2,
                                                                 boolean checkMem,
                                                                 boolean checkFLOPs,
                                                                 long FPfactor,
                                                                 int k)
      • isUltraSparseMatrixMult

        public static boolean isUltraSparseMatrixMult​(MatrixBlock m1,
                                                      MatrixBlock m2,
                                                      boolean m1Perm)
      • isSparseOutputMatrixMult

        public static boolean isSparseOutputMatrixMult​(MatrixBlock m1,
                                                       MatrixBlock m2)
      • isOuterProductTSMM

        public static boolean isOuterProductTSMM​(int rlen,
                                                 int clen,
                                                 boolean left)