Public

If the given result is different to cublasStatus.CUBLAS_STATUS_SUCCESS and
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checkResult

Obtain the current CUBLAS status by calling cublasGetErrorNative, and store the
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checkResultBLAS

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cublasCdotcNative

cublasCdotuNative

cublasCgbmvNative

cublasCgemmNative

cublasCgemvNative

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cublasCgeruNative

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cublasChemvNative

cublasCher2Native

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Gson

Finding current android device location

A border layout lays out a container, arranging and resizing its components to
fit in five regions: 

java.awt.BorderLayout

Thrown when a program encounters the end of a file or stream during an input
operation.

java.io.EOFException

An interface for an object which represents a database table entry, returned as
the result of the qu

java.sql.ResultSet

A concrete subclass of NumberFormat that formats decimal numbers. It has a
variety of features desig

java.text.DecimalFormat

Thrown when trying to retrieve an element past the end of an Enumeration or
Iterator.

java.util.NoSuchElementException

An interface for the creation of Connection objects which represent a connection
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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