Public

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

cublasAllocNative

cublasCaxpyNative

cublasCcopyNative

cublasCdotcNative

cublasCdotuNative

cublasCgbmvNative

cublasCgemmNative

cublasCgemvNative

cublasCgercNative

cublasCgeruNative

cublasChbmvNative

cublasChemmNative

cublasChemvNative

cublasCher2Native

cublasCher2kNative

cublasCherNative

cublasCherkNative

cublasChpr2Native

Gson

Making http post requests using okhttp

java.awt.image.Kernel

Convenience class for writing character files. The constructors of this class
assume that the defaul

java.io.FileWriter

This class is used to encode a string using the format required by
application/x-www-form-urlencoded

java.net.URLEncoder

A buffer for bytes. A byte buffer can be created in either one of the following
ways: *  #allocate(i

java.nio.ByteBuffer

This class implements a vector of bits that grows as needed. Each component of
the bit set has a boo

java.util.BitSet

A java.util.Queue that additionally supports operations that wait for the queue
to become non-empty 

java.util.concurrent.BlockingQueue

getResourceAsStream

notifyDataSetChanged

getSharedPreferences

/**
     * <pre>
     * void
     * cublasDsymv (char uplo, int n, double alpha, const double *A, int lda,
     *              const double *x, int incx, double beta, double *y, int incy)
     *
     * performs the matrix-vector operation
     *
     *     y = alpha*A*x + beta*y
     *
     * Alpha and beta are double precision scalars, and x and y are double
     * precision vectors, each with n elements. A is a symmetric n x n matrix
     * consisting of double precision elements that is stored in either upper or
     * lower storage mode.
     *
     * Input
     * -----
     * uplo   specifies whether the upper or lower triangular part of the array A
     *        is to be referenced. If uplo == 'U' or 'u', the symmetric matrix A
     *        is stored in upper storage mode, i.e. only the upper triangular part
     *        of A is to be referenced while the lower triangular part of A is to
     *        be inferred. If uplo == 'L' or 'l', the symmetric matrix A is stored
     *        in lower storage mode, i.e. only the lower triangular part of A is
     *        to be referenced while the upper triangular part of A is to be
     *        inferred.
     * n      specifies the number of rows and the number of columns of the
     *        symmetric matrix A. n must be at least zero.
     * alpha  double precision scalar multiplier applied to A*x.
     * A      double precision array of dimensions (lda, n). If uplo == 'U' or 'u',
     *        the leading n x n upper triangular part of the array A must contain
     *        the upper triangular part of the symmetric matrix and the strictly
     *        lower triangular part of A is not referenced. If uplo == 'L' or 'l',
     *        the leading n x n lower triangular part of the array A must contain
     *        the lower triangular part of the symmetric matrix and the strictly
     *        upper triangular part of A is not referenced.
     * lda    leading dimension of A. It must be at least max (1, n).
     * x      double precision array of length at least (1 + (n - 1) * abs(incx)).
     * incx   storage spacing between elements of x. incx must not be zero.
     * beta   double precision scalar multiplier applied to vector y.
     * y      double precision array of length at least (1 + (n - 1) * abs(incy)).
     *        If beta is zero, y is not read.
     * incy   storage spacing between elements of y. incy must not be zero.
     *
     * Output
     * ------
     * y      updated according to y = alpha*A*x + beta*y
     *
     * Reference: http://www.netlib.org/blas/dsymv.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 n < 0, or if incx or incy == 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 
   * cublasDsymv (char uplo, int n, double alpha, const double *A, int lda, 
   *              const double *x, int incx, double beta, double *y, int incy)
   *
   * performs the matrix-vector operation
   *
   *     y = alpha*A*x + beta*y
   *
   * Alpha and beta are double precision scalars, and x and y are double 
   * precision vectors, each with n elements. A is a symmetric n x n matrix 
   * consisting of double precision elements that is stored in either upper or 
   * lower storage mode.
   *
   * Input
   * -----
   * uplo   specifies whether the upper or lower triangular part of the array A 
   *        is to be referenced. If uplo == 'U' or 'u', the symmetric matrix A 
   *        is stored in upper storage mode, i.e. only the upper triangular part
   *        of A is to be referenced while the lower triangular part of A is to 
   *        be inferred. If uplo == 'L' or 'l', the symmetric matrix A is stored
   *        in lower storage mode, i.e. only the lower triangular part of A is 
   *        to be referenced while the upper triangular part of A is to be 
   *        inferred.
   * n      specifies the number of rows and the number of columns of the 
   *        symmetric matrix A. n must be at least zero.
   * alpha  double precision scalar multiplier applied to A*x.
   * A      double precision array of dimensions (lda, n). If uplo == 'U' or 'u',
   *        the leading n x n upper triangular part of the array A must contain
   *        the upper triangular part of the symmetric matrix and the strictly
   *        lower triangular part of A is not referenced. If uplo == 'L' or 'l',
   *        the leading n x n lower triangular part of the array A must contain
   *        the lower triangular part of the symmetric matrix and the strictly
   *        upper triangular part of A is not referenced. 
   * lda    leading dimension of A. It must be at least max (1, n).
   * x      double precision array of length at least (1 + (n - 1) * abs(incx)).
   * incx   storage spacing between elements of x. incx must not be zero.
   * beta   double precision scalar multiplier applied to vector y.
   * y      double precision array of length at least (1 + (n - 1) * abs(incy)). 
   *        If beta is zero, y is not read. 
   * incy   storage spacing between elements of y. incy must not be zero.
   *
   * Output
   * ------
   * y      updated according to y = alpha*A*x + beta*y
   *
   * Reference: http://www.netlib.org/blas/dsymv.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 n < 0, or if incx or incy == 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 cublasDsymvNativemethodin jcuda.jcublas.JCublas

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How to use
cublasDsymvNative
method
in
jcuda.jcublas.JCublas