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 collection that associates an ordered pair of keys, called a row key and a
column key, with a sing

com.google.common.collect.Table

A writable sink for bytes.Most clients will use output streams that write data
to the file system ( 

java.io.OutputStream

HashMap is an implementation of Map. All optional operations are supported.All
elements are permitte

java.util.HashMap

LinkedHashMap is an implementation of Map that guarantees iteration order. All
optional operations a

java.util.LinkedHashMap

An interface for the creation of Connection objects which represent a connection
to a database. This

javax.sql.DataSource

General IO stream manipulation utilities. This class provides static utility
methods for input/outpu

org.apache.commons.io.IOUtils

setScale

compareTo

Return the contained value, if present, otherwise throw an exception to be
created by the provided s

orElseThrow

/**
     * <pre>
     * void
     * cublasCsyrk (char uplo, char trans, int n, int k, cuComplex alpha,
     *              const cuComplex *A, int lda, cuComplex beta, cuComplex *C, int ldc)
     *
     * performs one of the symmetric rank k operations
     *
     *   C = alpha * A * transpose(A) + beta * C, or
     *   C = alpha * transpose(A) * A + beta * C.
     *
     * Alpha and beta are single precision complex scalars. C is an n x n symmetric matrix
     * consisting of single precision complex elements and stored in either lower or
     * upper storage mode. A is a matrix consisting of single precision complex elements
     * with dimension of n x k in the first case, and k x n in the second case.
     *
     * Input
     * -----
     * uplo   specifies whether the symmetric matrix C 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.
     * trans  specifies the operation to be performed. If trans == 'N' or 'n', C =
     *        alpha * transpose(A) + beta * C. If trans == 'T', 't', 'C', or 'c',
     *        C = transpose(A) * A + beta * C.
     * n      specifies the number of rows and the number columns of matrix C. If
     *        trans == 'N' or 'n', n specifies the number of rows of matrix A. If
     *        trans == 'T', 't', 'C', or 'c', n specifies the columns of matrix A.
     *        n must be at least zero.
     * k      If trans == 'N' or 'n', k specifies the number of rows of matrix A.
     *        If trans == 'T', 't', 'C', or 'c', k specifies the number of rows of
     *        matrix A. k must be at least zero.
     * alpha  single precision complex scalar multiplier applied to A * transpose(A) or
     *        transpose(A) * A.
     * A      single precision complex array of dimensions (lda, ka), where ka is k when
     *        trans == 'N' or 'n', and is n otherwise. When trans == 'N' or 'n',
     *        the leading n x k part of array A must contain the matrix A,
     *        otherwise the leading k x n part of the array must contains the
     *        matrix A.
     * lda    leading dimension of A. When trans == 'N' or 'n' then lda must be at
     *        least max(1, n). Otherwise lda must be at least max(1, k).
     * beta   single precision complex scalar multiplier applied to C. If beta izs zero, C
     *        does not have to be a valid input
     * C      single precision complex array of dimensions (ldc, n). If uplo = 'U' or 'u',
     *        the leading n x n triangular part of the array C must contain the
     *        upper triangular part of the symmetric matrix C and the strictly
     *        lower triangular part of C is not referenced. On exit, the upper
     *        triangular part of C is overwritten by the upper triangular part of
     *        the updated matrix. If uplo = 'L' or 'l', the leading n x n
     *        triangular part of the array C must contain the lower triangular part
     *        of the symmetric matrix C and the strictly upper triangular part of C
     *        is not referenced. On exit, the lower triangular part of C is
     *        overwritten by the lower triangular part of the updated matrix.
     * ldc    leading dimension of C. It must be at least max(1, n).
     *
     * Output
     * ------
     * C      updated according to C = alpha * A * transpose(A) + beta * C, or C =
     *        alpha * transpose(A) * A + beta * C
     *
     * Reference: http://www.netlib.org/blas/csyrk.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 k < 0
     * CUBLAS_STATUS_EXECUTION_FAILED if function failed to launch on GPU
     * </pre>
     */

/**
   * <pre>
   * void 
   * cublasCsyrk (char uplo, char trans, int n, int k, cuComplex alpha, 
   *              const cuComplex *A, int lda, cuComplex beta, cuComplex *C, int ldc)
   *
   * performs one of the symmetric rank k operations
   * 
   *   C = alpha * A * transpose(A) + beta * C, or 
   *   C = alpha * transpose(A) * A + beta * C.
   *
   * Alpha and beta are single precision complex scalars. C is an n x n symmetric matrix 
   * consisting of single precision complex elements and stored in either lower or 
   * upper storage mode. A is a matrix consisting of single precision complex elements
   * with dimension of n x k in the first case, and k x n in the second case.
   *
   * Input
   * -----
   * uplo   specifies whether the symmetric matrix C 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.
   * trans  specifies the operation to be performed. If trans == 'N' or 'n', C = 
   *        alpha * transpose(A) + beta * C. If trans == 'T', 't', 'C', or 'c', 
   *        C = transpose(A) * A + beta * C.
   * n      specifies the number of rows and the number columns of matrix C. If 
   *        trans == 'N' or 'n', n specifies the number of rows of matrix A. If 
   *        trans == 'T', 't', 'C', or 'c', n specifies the columns of matrix A. 
   *        n must be at least zero.
   * k      If trans == 'N' or 'n', k specifies the number of rows of matrix A. 
   *        If trans == 'T', 't', 'C', or 'c', k specifies the number of rows of 
   *        matrix A. k must be at least zero.
   * alpha  single precision complex scalar multiplier applied to A * transpose(A) or 
   *        transpose(A) * A.
   * A      single precision complex array of dimensions (lda, ka), where ka is k when 
   *        trans == 'N' or 'n', and is n otherwise. When trans == 'N' or 'n', 
   *        the leading n x k part of array A must contain the matrix A, 
   *        otherwise the leading k x n part of the array must contains the 
   *        matrix A.
   * lda    leading dimension of A. When trans == 'N' or 'n' then lda must be at
   *        least max(1, n). Otherwise lda must be at least max(1, k).
   * beta   single precision complex scalar multiplier applied to C. If beta izs zero, C
   *        does not have to be a valid input
   * C      single precision complex array of dimensions (ldc, n). If uplo = 'U' or 'u',
   *        the leading n x n triangular part of the array C must contain the 
   *        upper triangular part of the symmetric matrix C and the strictly 
   *        lower triangular part of C is not referenced. On exit, the upper 
   *        triangular part of C is overwritten by the upper triangular part of 
   *        the updated matrix. If uplo = 'L' or 'l', the leading n x n 
   *        triangular part of the array C must contain the lower triangular part
   *        of the symmetric matrix C and the strictly upper triangular part of C
   *        is not referenced. On exit, the lower triangular part of C is 
   *        overwritten by the lower triangular part of the updated matrix.
   * ldc    leading dimension of C. It must be at least max(1, n).
   *
   * Output
   * ------
   * C      updated according to C = alpha * A * transpose(A) + beta * C, or C = 
   *        alpha * transpose(A) * A + beta * C
   *
   * Reference: http://www.netlib.org/blas/csyrk.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 k < 0
    * CUBLAS_STATUS_EXECUTION_FAILED if function failed to launch on GPU
    * </pre>
    */

How to use cublasCsyrkNativemethodin jcuda.jcublas.JCublas

Best Java code snippets using jcuda.jcublas.JCublas.cublasCsyrkNative (Showing top 6 results out of 315)

How to use
cublasCsyrkNative
method
in
jcuda.jcublas.JCublas