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

Reactive rest calls using spring rest template

A flow layout arranges components in a left-to-right flow, much like lines of
text in a paragraph. F

java.awt.FlowLayout

This exception is thrown when a timeout expired on a socket read or accept
operation.

java.net.SocketTimeoutException

A controller for the selection of SelectableChannel objects. Selectable channels
can be registered w

java.nio.channels.Selector

 Calendar is an abstract base class for converting between a Date object and a
set of integer fields

java.util.Calendar

A synchronization aid that allows one or more threads to wait until a set of
operations being perfor

java.util.concurrent.CountDownLatch

scala.Option

scheduleAtFixedRate

onRequestPermissionsResult

Return the original filename in the client's filesystem.This may contain path
information depending 

getOriginalFilename

/**
     * <pre>
     * void
     * cublasDgbmv (char trans, int m, int n, int kl, int ku, double alpha,
     *              const double *A, int lda, const double *x, int incx, double beta,
     *              double *y, int incy);
     *
     * performs one of the matrix-vector operations
     *
     *    y = alpha*op(A)*x + beta*y,  op(A)=A or op(A) = transpose(A)
     *
     * alpha and beta are double precision scalars. x and y are double precision
     * vectors. A is an m by n band matrix consisting of double precision elements
     * with kl sub-diagonals and ku super-diagonals.
     *
     * Input
     * -----
     * trans  specifies op(A). If trans == 'N' or 'n', op(A) = A. If trans == 'T',
     *        't', 'C', or 'c', op(A) = transpose(A)
     * m      specifies the number of rows of the matrix A. m must be at least
     *        zero.
     * n      specifies the number of columns of the matrix A. n must be at least
     *        zero.
     * kl     specifies the number of sub-diagonals of matrix A. It must be at
     *        least zero.
     * ku     specifies the number of super-diagonals of matrix A. It must be at
     *        least zero.
     * alpha  double precision scalar multiplier applied to op(A).
     * A      double precision array of dimensions (lda, n). The leading
     *        (kl + ku + 1) x n part of the array A must contain the band matrix A,
     *        supplied column by column, with the leading diagonal of the matrix
     *        in row (ku + 1) of the array, the first super-diagonal starting at
     *        position 2 in row ku, the first sub-diagonal starting at position 1
     *        in row (ku + 2), and so on. Elements in the array A that do not
     *        correspond to elements in the band matrix (such as the top left
     *        ku x ku triangle) are not referenced.
     * lda    leading dimension of A. lda must be at least (kl + ku + 1).
     * x      double precision array of length at least (1+(n-1)*abs(incx)) when
     *        trans == 'N' or 'n' and at least (1+(m-1)*abs(incx)) otherwise.
     * incx   specifies the increment for the elements of x. incx must not be zero.
     * beta   double precision scalar multiplier applied to vector y. If beta is
     *        zero, y is not read.
     * y      double precision array of length at least (1+(m-1)*abs(incy)) when
     *        trans == 'N' or 'n' and at least (1+(n-1)*abs(incy)) otherwise. If
     *        beta is zero, y is not read.
     * incy   On entry, incy specifies the increment for the elements of y. incy
     *        must not be zero.
     *
     * Output
     * ------
     * y      updated according to y = alpha*op(A)*x + beta*y
     *
     * Reference: http://www.netlib.org/blas/dgbmv.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 
   * cublasDgbmv (char trans, int m, int n, int kl, int ku, double alpha,
   *              const double *A, int lda, const double *x, int incx, double beta,
   *              double *y, int incy);
   *
   * performs one of the matrix-vector operations
   *
   *    y = alpha*op(A)*x + beta*y,  op(A)=A or op(A) = transpose(A)
   *
   * alpha and beta are double precision scalars. x and y are double precision
   * vectors. A is an m by n band matrix consisting of double precision elements
   * with kl sub-diagonals and ku super-diagonals.
   *
   * Input
   * -----
   * trans  specifies op(A). If trans == 'N' or 'n', op(A) = A. If trans == 'T', 
   *        't', 'C', or 'c', op(A) = transpose(A)
   * m      specifies the number of rows of the matrix A. m must be at least 
   *        zero.
   * n      specifies the number of columns of the matrix A. n must be at least
   *        zero.
   * kl     specifies the number of sub-diagonals of matrix A. It must be at 
   *        least zero.
   * ku     specifies the number of super-diagonals of matrix A. It must be at
   *        least zero.
   * alpha  double precision scalar multiplier applied to op(A).
   * A      double precision array of dimensions (lda, n). The leading
   *        (kl + ku + 1) x n part of the array A must contain the band matrix A,
   *        supplied column by column, with the leading diagonal of the matrix 
   *        in row (ku + 1) of the array, the first super-diagonal starting at 
   *        position 2 in row ku, the first sub-diagonal starting at position 1
   *        in row (ku + 2), and so on. Elements in the array A that do not 
   *        correspond to elements in the band matrix (such as the top left 
   *        ku x ku triangle) are not referenced.
   * lda    leading dimension of A. lda must be at least (kl + ku + 1).
   * x      double precision array of length at least (1+(n-1)*abs(incx)) when 
   *        trans == 'N' or 'n' and at least (1+(m-1)*abs(incx)) otherwise.
   * incx   specifies the increment for the elements of x. incx must not be zero.
   * beta   double precision scalar multiplier applied to vector y. If beta is 
   *        zero, y is not read.
   * y      double precision array of length at least (1+(m-1)*abs(incy)) when 
   *        trans == 'N' or 'n' and at least (1+(n-1)*abs(incy)) otherwise. If 
   *        beta is zero, y is not read.
   * incy   On entry, incy specifies the increment for the elements of y. incy 
   *        must not be zero.
   *
   * Output
   * ------
   * y      updated according to y = alpha*op(A)*x + beta*y
   *
   * Reference: http://www.netlib.org/blas/dgbmv.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 cublasDgbmvNativemethodin jcuda.jcublas.JCublas

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How to use
cublasDgbmvNative
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jcuda.jcublas.JCublas