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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

checkResultBLAS

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cublasChbmvNative

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cublasChemvNative

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Gson

Start an intent from android

An Internet Protocol (IP) address. This can be either an IPv4 address or an IPv6
address, and in pra

java.net.InetAddress

 KeyStore is responsible for maintaining cryptographic keys and their owners. 
The type of the syste

java.security.KeyStore

Java representation of an SQL TIME value. Provides utilities to format and parse
the time's represen

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An ordered collection (also known as a sequence). The user of this interface has
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A sequence of elements supporting sequential and parallel aggregate operations.
The following exampl

java.util.stream.Stream

Provides an abstract class to be subclassed to create an HTTP servlet suitable
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javax.servlet.http.HttpServlet

getSystemService

setRequestProperty

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/**
     * <pre>
     * void
     * cublasDsyrk (char uplo, char trans, int n, int k, double alpha,
     *              const double *A, int lda, double beta, double *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 double precision scalars. C is an n x n symmetric matrix
     * consisting of double precision elements and stored in either lower or
     * upper storage mode. A is a matrix consisting of double precision 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  double precision scalar multiplier applied to A * transpose(A) or
     *        transpose(A) * A.
     * A      double precision 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   double precision scalar multiplier applied to C. If beta izs zero, C
     *        does not have to be a valid input
     * C      double precision 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/dsyrk.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_ARCH_MISMATCH    if invoked on device without DP support
     * CUBLAS_STATUS_EXECUTION_FAILED if function failed to launch on GPU
     * </pre>
     */

/**
   * <pre>
   * void 
   * cublasDsyrk (char uplo, char trans, int n, int k, double alpha, 
   *              const double *A, int lda, double beta, double *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 double precision scalars. C is an n x n symmetric matrix 
   * consisting of double precision elements and stored in either lower or 
   * upper storage mode. A is a matrix consisting of double precision 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  double precision scalar multiplier applied to A * transpose(A) or 
   *        transpose(A) * A.
   * A      double precision 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   double precision scalar multiplier applied to C. If beta izs zero, C
   *        does not have to be a valid input
   * C      double precision 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/dsyrk.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_ARCH_MISMATCH    if invoked on device without DP support
    * CUBLAS_STATUS_EXECUTION_FAILED if function failed to launch on GPU
    * </pre>
    */

How to use cublasDsyrkNativemethodin jcuda.jcublas.JCublas

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How to use
cublasDsyrkNative
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