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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

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Gson

Start an intent from android

Provides an abstract class to be subclassed to create an HTTP servlet suitable
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javax.swing.JFrame

javax.swing.JList

This is the central class in the log4j package. Most logging operations, except
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org.apache.log4j.Logger

Abstract superclass of object loading (and querying) strategies. This class
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/**
     * <pre>
     * void
     * cublasCsymm (char side, char uplo, int m, int n, cuComplex alpha,
     *              const cuComplex *A, int lda, const cuComplex *B, int ldb,
     *              cuComplex beta, cuComplex *C, int ldc);
     *
     * performs one of the matrix-matrix operations
     *
     *   C = alpha * A * B + beta * C, or
     *   C = alpha * B * A + beta * C,
     *
     * where alpha and beta are single precision complex scalars, A is a symmetric matrix
     * consisting of single precision complex elements and stored in either lower or upper
     * storage mode, and B and C are m x n matrices consisting of single precision
     * complex elements.
     *
     * Input
     * -----
     * side   specifies whether the symmetric matrix A appears on the left side
     *        hand side or right hand side of matrix B, as follows. If side == 'L'
     *        or 'l', then C = alpha * A * B + beta * C. If side = 'R' or 'r',
     *        then C = alpha * B * A + beta * C.
     * uplo   specifies whether the symmetric matrix A is stored in upper or lower
     *        storage mode, as follows. If uplo == 'U' or 'u', only the upper
     *        triangular part of the symmetric matrix is to be referenced, and the
     *        elements of the strictly lower triangular part are to be infered from
     *        those in the upper triangular part. If uplo == 'L' or 'l', only the
     *        lower triangular part of the symmetric matrix is to be referenced,
     *        and the elements of the strictly upper triangular part are to be
     *        infered from those in the lower triangular part.
     * m      specifies the number of rows of the matrix C, and the number of rows
     *        of matrix B. It also specifies the dimensions of symmetric matrix A
     *        when side == 'L' or 'l'. m must be at least zero.
     * n      specifies the number of columns of the matrix C, and the number of
     *        columns of matrix B. It also specifies the dimensions of symmetric
     *        matrix A when side == 'R' or 'r'. n must be at least zero.
     * alpha  single precision scalar multiplier applied to A * B, or B * A
     * A      single precision array of dimensions (lda, ka), where ka is m when
     *        side == 'L' or 'l' and is n otherwise. If side == 'L' or 'l' the
     *        leading m x m part of array A must contain the symmetric matrix,
     *        such that when uplo == 'U' or 'u', the leading m x m part stores the
     *        upper triangular part of the symmetric matrix, and the strictly lower
     *        triangular part of A is not referenced, and when uplo == 'U' or 'u',
     *        the leading m x m part stores the lower triangular part of the
     *        symmetric matrix and the strictly upper triangular part is not
     *        referenced. If side == 'R' or 'r' the leading n x n part of array A
     *        must contain the symmetric matrix, such that when uplo == 'U' or 'u',
     *        the leading n x n part stores the upper triangular part of the
     *        symmetric matrix and the strictly lower triangular part of A is not
     *        referenced, and when uplo == 'U' or 'u', the leading n x n part
     *        stores the lower triangular part of the symmetric matrix and the
     *        strictly upper triangular part is not referenced.
     * lda    leading dimension of A. When side == 'L' or 'l', it must be at least
     *        max(1, m) and at least max(1, n) otherwise.
     * B      single precision array of dimensions (ldb, n). On entry, the leading
     *        m x n part of the array contains the matrix B.
     * ldb    leading dimension of B. It must be at least max (1, m).
     * beta   single precision scalar multiplier applied to C. If beta is zero, C
     *        does not have to be a valid input
     * C      single precision array of dimensions (ldc, n)
     * ldc    leading dimension of C. Must be at least max(1, m)
     *
     * Output
     * ------
     * C      updated according to C = alpha * A * B + beta * C, or C = alpha *
     *        B * A + beta * C
     *
     * Reference: http://www.netlib.org/blas/csymm.f
     *
     * Error status for this function can be retrieved via cublasGetError().
     *
     * Error Status
     * ------------
     * CUBLAS_STATUS_NOT_INITIALIZED  if CUBLAS library has not been initialized
     * CUBLAS_STATUS_INVALID_VALUE    if m or n are < 0
     * CUBLAS_STATUS_EXECUTION_FAILED if function failed to launch on GPU
     * </pre>
     */

/**
   * <pre>
   * void 
   * cublasCsymm (char side, char uplo, int m, int n, cuComplex alpha, 
   *              const cuComplex *A, int lda, const cuComplex *B, int ldb, 
   *              cuComplex beta, cuComplex *C, int ldc);
   *
   * performs one of the matrix-matrix operations
   * 
   *   C = alpha * A * B + beta * C, or 
   *   C = alpha * B * A + beta * C,
   *
   * where alpha and beta are single precision complex scalars, A is a symmetric matrix
   * consisting of single precision complex elements and stored in either lower or upper 
   * storage mode, and B and C are m x n matrices consisting of single precision
   * complex elements.
   *
   * Input
   * -----
   * side   specifies whether the symmetric matrix A appears on the left side 
   *        hand side or right hand side of matrix B, as follows. If side == 'L' 
   *        or 'l', then C = alpha * A * B + beta * C. If side = 'R' or 'r', 
   *        then C = alpha * B * A + beta * C.
   * uplo   specifies whether the symmetric matrix A is stored in upper or lower 
   *        storage mode, as follows. If uplo == 'U' or 'u', only the upper 
   *        triangular part of the symmetric matrix is to be referenced, and the 
   *        elements of the strictly lower triangular part are to be infered from
   *        those in the upper triangular part. If uplo == 'L' or 'l', only the 
   *        lower triangular part of the symmetric matrix is to be referenced, 
   *        and the elements of the strictly upper triangular part are to be 
   *        infered from those in the lower triangular part.
   * m      specifies the number of rows of the matrix C, and the number of rows
   *        of matrix B. It also specifies the dimensions of symmetric matrix A 
   *        when side == 'L' or 'l'. m must be at least zero.
   * n      specifies the number of columns of the matrix C, and the number of 
   *        columns of matrix B. It also specifies the dimensions of symmetric 
   *        matrix A when side == 'R' or 'r'. n must be at least zero.
   * alpha  single precision scalar multiplier applied to A * B, or B * A
   * A      single precision array of dimensions (lda, ka), where ka is m when 
   *        side == 'L' or 'l' and is n otherwise. If side == 'L' or 'l' the 
   *        leading m x m part of array A must contain the symmetric matrix, 
   *        such that when uplo == 'U' or 'u', the leading m x m part stores the 
   *        upper triangular part of the symmetric matrix, and the strictly lower
   *        triangular part of A is not referenced, and when uplo == 'U' or 'u', 
   *        the leading m x m part stores the lower triangular part of the 
   *        symmetric matrix and the strictly upper triangular part is not 
   *        referenced. If side == 'R' or 'r' the leading n x n part of array A 
   *        must contain the symmetric matrix, such that when uplo == 'U' or 'u',
   *        the leading n x n part stores the upper triangular part of the 
   *        symmetric matrix and the strictly lower triangular part of A is not 
   *        referenced, and when uplo == 'U' or 'u', the leading n x n part 
   *        stores the lower triangular part of the symmetric matrix and the 
   *        strictly upper triangular part is not referenced.
   * lda    leading dimension of A. When side == 'L' or 'l', it must be at least 
   *        max(1, m) and at least max(1, n) otherwise.
   * B      single precision array of dimensions (ldb, n). On entry, the leading
   *        m x n part of the array contains the matrix B.
   * ldb    leading dimension of B. It must be at least max (1, m).
   * beta   single precision scalar multiplier applied to C. If beta is zero, C 
   *        does not have to be a valid input
   * C      single precision array of dimensions (ldc, n)
   * ldc    leading dimension of C. Must be at least max(1, m)
   *
   * Output
   * ------
   * C      updated according to C = alpha * A * B + beta * C, or C = alpha * 
   *        B * A + beta * C
   *
   * Reference: http://www.netlib.org/blas/csymm.f
   *
   * Error status for this function can be retrieved via cublasGetError().
  *
    * Error Status
    * ------------
    * CUBLAS_STATUS_NOT_INITIALIZED  if CUBLAS library has not been initialized
    * CUBLAS_STATUS_INVALID_VALUE    if m or n are < 0
    * CUBLAS_STATUS_EXECUTION_FAILED if function failed to launch on GPU
    * </pre>
    */

How to use cublasCsymmNativemethodin jcuda.jcublas.JCublas

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How to use
cublasCsymmNative
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jcuda.jcublas.JCublas