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If the given result is different to cublasStatus.CUBLAS_STATUS_SUCCESS and
exceptions have been enab

checkResult

Obtain the current CUBLAS status by calling cublasGetErrorNative, and store the
result as the lastRe

checkResultBLAS

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Updating database using SQL prepared statement

This Graphics2D class extends the Graphics class to provide more sophisticated
control overgraphics 

java.awt.Graphics2D

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default layout for a windo

java.awt.Window

This exception is thrown when a timeout expired on a socket read or accept
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java.net.SocketTimeoutException

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for new implementatio

java.util.Dictionary

LinkedHashMap is an implementation of Map that guarantees iteration order. All
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/**
     * <pre>
     * void
     * cublasDgemm (char transa, char transb, int m, int n, int k, double alpha,
     *              const double *A, int lda, const double *B, int ldb,
     *              double beta, double *C, int ldc)
     *
     * computes the product of matrix A and matrix B, multiplies the result
     * by scalar alpha, and adds the sum to the product of matrix C and
     * scalar beta. It performs one of the matrix-matrix operations:
     *
     * C = alpha * op(A) * op(B) + beta * C,
     * where op(X) = X or op(X) = transpose(X),
     *
     * and alpha and beta are double-precision scalars. A, B and C are matrices
     * consisting of double-precision elements, with op(A) an m x k matrix,
     * op(B) a k x n matrix, and C an m x n matrix. Matrices A, B, and C are
     * stored in column-major format, and lda, ldb, and ldc are the leading
     * dimensions of the two-dimensional arrays containing A, B, and C.
     *
     * Input
     * -----
     * transa specifies op(A). If transa == 'N' or 'n', op(A) = A.
     *        If transa == 'T', 't', 'C', or 'c', op(A) = transpose(A).
     * transb specifies op(B). If transb == 'N' or 'n', op(B) = B.
     *        If transb == 'T', 't', 'C', or 'c', op(B) = transpose(B).
     * m      number of rows of matrix op(A) and rows of matrix C; m must be at
     *        least zero.
     * n      number of columns of matrix op(B) and number of columns of C;
     *        n must be at least zero.
     * k      number of columns of matrix op(A) and number of rows of op(B);
     *        k must be at least zero.
     * alpha  double-precision scalar multiplier applied to op(A) * op(B).
     * A      double-precision array of dimensions (lda, k) if transa == 'N' or
     *        'n', and of dimensions (lda, m) otherwise. If transa == 'N' or
     *        'n' lda must be at least max(1, m), otherwise lda must be at
     *        least max(1, k).
     * lda    leading dimension of two-dimensional array used to store matrix A.
     * B      double-precision array of dimensions (ldb, n) if transb == 'N' or
     *        'n', and of dimensions (ldb, k) otherwise. If transb == 'N' or
     *        'n' ldb must be at least max (1, k), otherwise ldb must be at
     *        least max(1, n).
     * ldb    leading dimension of two-dimensional array used to store matrix B.
     * beta   double-precision scalar multiplier applied to C. If zero, C does not
     *        have to be a valid input
     * C      double-precision array of dimensions (ldc, n); ldc must be at least
     *        max(1, m).
     * ldc    leading dimension of two-dimensional array used to store matrix C.
     *
     * Output
     * ------
     * C      updated based on C = alpha * op(A)*op(B) + beta * C.
     *
     * Reference: http://www.netlib.org/blas/sgemm.f
     *
     * Error status for this function can be retrieved via cublasGetError().
     *
     * Error Status
     * ------------
     * CUBLAS_STATUS_NOT_INITIALIZED  if CUBLAS was not initialized
     * CUBLAS_STATUS_INVALID_VALUE    if m < 0, n < 0, or k < 0
     * CUBLAS_STATUS_ARCH_MISMATCH    if invoked on device without DP support
     * CUBLAS_STATUS_EXECUTION_FAILED if function failed to launch on GPU
     * </pre>
     */

/**
   * <pre>
   * void 
   * cublasDgemm (char transa, char transb, int m, int n, int k, double alpha,
   *              const double *A, int lda, const double *B, int ldb, 
   *              double beta, double *C, int ldc)
   *
   * computes the product of matrix A and matrix B, multiplies the result 
   * by scalar alpha, and adds the sum to the product of matrix C and
   * scalar beta. It performs one of the matrix-matrix operations:
   *
   * C = alpha * op(A) * op(B) + beta * C,  
   * where op(X) = X or op(X) = transpose(X),
   *
   * and alpha and beta are double-precision scalars. A, B and C are matrices
   * consisting of double-precision elements, with op(A) an m x k matrix, 
   * op(B) a k x n matrix, and C an m x n matrix. Matrices A, B, and C are 
   * stored in column-major format, and lda, ldb, and ldc are the leading 
   * dimensions of the two-dimensional arrays containing A, B, and C.
   *
   * Input
   * -----
   * transa specifies op(A). If transa == 'N' or 'n', op(A) = A. 
   *        If transa == 'T', 't', 'C', or 'c', op(A) = transpose(A).
   * transb specifies op(B). If transb == 'N' or 'n', op(B) = B. 
   *        If transb == 'T', 't', 'C', or 'c', op(B) = transpose(B).
   * m      number of rows of matrix op(A) and rows of matrix C; m must be at
   *        least zero.
   * n      number of columns of matrix op(B) and number of columns of C; 
   *        n must be at least zero.
   * k      number of columns of matrix op(A) and number of rows of op(B);
   *        k must be at least zero.
   * alpha  double-precision scalar multiplier applied to op(A) * op(B).
   * A      double-precision array of dimensions (lda, k) if transa == 'N' or 
   *        'n', and of dimensions (lda, m) otherwise. If transa == 'N' or 
   *        'n' lda must be at least max(1, m), otherwise lda must be at
   *        least max(1, k).
   * lda    leading dimension of two-dimensional array used to store matrix A.
   * B      double-precision array of dimensions (ldb, n) if transb == 'N' or
   *        'n', and of dimensions (ldb, k) otherwise. If transb == 'N' or 
   *        'n' ldb must be at least max (1, k), otherwise ldb must be at
   *        least max(1, n).
   * ldb    leading dimension of two-dimensional array used to store matrix B.
   * beta   double-precision scalar multiplier applied to C. If zero, C does not 
   *        have to be a valid input
   * C      double-precision array of dimensions (ldc, n); ldc must be at least
   *        max(1, m).
   * ldc    leading dimension of two-dimensional array used to store matrix C.
   * 
   * Output
   * ------
   * C      updated based on C = alpha * op(A)*op(B) + beta * C.
   *
   * Reference: http://www.netlib.org/blas/sgemm.f
   *
   * Error status for this function can be retrieved via cublasGetError().
   * 
   * Error Status
   * ------------
   * CUBLAS_STATUS_NOT_INITIALIZED  if CUBLAS was not initialized
   * CUBLAS_STATUS_INVALID_VALUE    if m < 0, n < 0, or k < 0
   * CUBLAS_STATUS_ARCH_MISMATCH    if invoked on device without DP support
   * CUBLAS_STATUS_EXECUTION_FAILED if function failed to launch on GPU
   * </pre>
   */

How to use cublasDgemmNativemethodin jcuda.jcublas.JCublas

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How to use
cublasDgemmNative
method
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jcuda.jcublas.JCublas