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

An abstraction for a native pointer data type. A Pointer instance represents, on
the Java side, a na

com.sun.jna.Pointer

Represents a command that can be executed. Often used to run code in a different
Thread.

java.lang.Runnable

A connection represents a link from a Java application to a database. All SQL
statements and results

java.sql.Connection

DecimalFormat is a concrete subclass ofNumberFormat that formats decimal
numbers. It has a variety o

java.text.DecimalFormat

Doubly-linked list implementation of the List and Dequeinterfaces. Implements
all optional list oper

java.util.LinkedList

A TimeUnit represents time durations at a given unit of granularity and provides
utility methods to 

java.util.concurrent.TimeUnit

startActivity

getApplicationContext

Creates and executes a periodic action that becomes enabled first after the
given initial delay, and

scheduleAtFixedRate

/**
     * <pre>
     * void
     * cublasCherk (char uplo, char trans, int n, int k, float alpha,
     *              const cuComplex *A, int lda, float beta, cuComplex *C, int ldc)
     *
     * performs one of the hermitian rank k operations
     *
     *   C = alpha * A * conjugate(transpose(A)) + beta * C, or
     *   C = alpha * conjugate(transpose(A)) * A + beta * C.
     *
     * Alpha and beta are single precision real scalars. C is an n x n hermitian 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 hermitian matrix C is stored in upper or lower
     *        storage mode as follows. If uplo == 'U' or 'u', only the upper
     *        triangular part of the hermitian 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 hermitian 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 * A * conjugate(transpose(A)) + beta * C. If trans == 'T', 't', 'C', or 'c',
     *        C = alpha * conjugate(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 columns 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 scalar multiplier applied to A * conjugate(transpose(A)) or
     *        conjugate(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 scalar multiplier applied to C. If beta is 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 hermitian 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 hermitian 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.
     *        The imaginary parts of the diagonal elements need
     *        not be set,  they are assumed to be zero,  and on exit they
     *        are set to zero.
     * ldc    leading dimension of C. It must be at least max(1, n).
     *
     * Output
     * ------
     * C      updated according to C = alpha * A * conjugate(transpose(A)) + beta * C, or C =
     *        alpha * conjugate(transpose(A)) * A + beta * C
     *
     * Reference: http://www.netlib.org/blas/cherk.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 
   * cublasCherk (char uplo, char trans, int n, int k, float alpha, 
   *              const cuComplex *A, int lda, float beta, cuComplex *C, int ldc)
   *
   * performs one of the hermitian rank k operations
   * 
   *   C = alpha * A * conjugate(transpose(A)) + beta * C, or 
   *   C = alpha * conjugate(transpose(A)) * A + beta * C.
   *
   * Alpha and beta are single precision real scalars. C is an n x n hermitian 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 hermitian matrix C is stored in upper or lower 
   *        storage mode as follows. If uplo == 'U' or 'u', only the upper 
   *        triangular part of the hermitian 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 hermitian 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 * A * conjugate(transpose(A)) + beta * C. If trans == 'T', 't', 'C', or 'c', 
   *        C = alpha * conjugate(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 columns 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 scalar multiplier applied to A * conjugate(transpose(A)) or 
   *        conjugate(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 scalar multiplier applied to C. If beta is 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 hermitian 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 hermitian 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.
   *        The imaginary parts of the diagonal elements need
   *        not be set,  they are assumed to be zero,  and on exit they
   *        are set to zero.
   * ldc    leading dimension of C. It must be at least max(1, n).
   *
   * Output
   * ------
   * C      updated according to C = alpha * A * conjugate(transpose(A)) + beta * C, or C = 
   *        alpha * conjugate(transpose(A)) * A + beta * C
   *
   * Reference: http://www.netlib.org/blas/cherk.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 cublasCherkNativemethodin jcuda.jcublas.JCublas

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How to use
cublasCherkNative
method
in
jcuda.jcublas.JCublas