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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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Gson

Parsing JSON documents to java classes using gson

A BufferedInputStream adds functionality to another input stream-namely, the
ability to buffer the i

java.io.BufferedInputStream

Wraps an existing Reader and buffers the input. Expensive interaction with the
underlying reader is 

java.io.BufferedReader

The abstract base class for all number formats. This class provides the
interface for formatting and

java.text.NumberFormat

Breaks a string into tokens; new code should probably use String#split.>  
// Legacy code: 
StringTo

java.util.StringTokenizer

A Handler object accepts a logging request and exports the desired messages to a
target, for example

java.util.logging.Handler

Provides Base64 encoding and decoding as defined by RFC 2045.This class
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org.apache.commons.codec.binary.Base64

setContentView

Return the contained value, if present, otherwise throw an exception to be
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orElseThrow

notifyDataSetChanged

/**
     * <pre>
     * void
     * cublasDsyr2k (char uplo, char trans, int n, int k, double alpha,
     *               const double *A, int lda, const double *B, int ldb,
     *               double beta, double *C, int ldc)
     *
     * performs one of the symmetric rank 2k operations
     *
     *    C = alpha * A * transpose(B) + alpha * B * transpose(A) + beta * C, or
     *    C = alpha * transpose(A) * B + alpha * transpose(B) * 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 and B are matrices 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 references,
     *        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 * transpose(B) + alpha * B * transpose(A) + beta * C,
     *        If trans == 'T', 't', 'C', or 'c', C = alpha * transpose(A) * B +
     *        alpha * transpose(B) * 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.
     * 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 contain 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).
     * B      double precision array of dimensions (lda, kb), where kb is k when
     *        trans == 'N' or 'n', and is n otherwise. When trans == 'N' or 'n',
     *        the leading n x k part of array B must contain the matrix B,
     *        otherwise the leading k x n part of the array must contain the matrix
     *        B.
     * ldb    leading dimension of N. When trans == 'N' or 'n' then ldb must be at
     *        least max(1, n). Otherwise ldb must be at least max(1, k).
     * beta   double precision scalar multiplier applied to C. If beta is 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. Must be at least max(1, n).
     *
     * Output
     * ------
     * C      updated according to alpha*A*transpose(B) + alpha*B*transpose(A) +
     *        beta*C or alpha*transpose(A)*B + alpha*transpose(B)*A + beta*C
     *
     * Reference:   http://www.netlib.org/blas/dsyr2k.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
   * cublasDsyr2k (char uplo, char trans, int n, int k, double alpha,
   *               const double *A, int lda, const double *B, int ldb,
   *               double beta, double *C, int ldc)
   *
   * performs one of the symmetric rank 2k operations
   *
   *    C = alpha * A * transpose(B) + alpha * B * transpose(A) + beta * C, or
   *    C = alpha * transpose(A) * B + alpha * transpose(B) * 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 and B are matrices 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 references,
   *        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 * transpose(B) + alpha * B * transpose(A) + beta * C,
   *        If trans == 'T', 't', 'C', or 'c', C = alpha * transpose(A) * B +
   *        alpha * transpose(B) * 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.
   * 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 contain 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).
   * B      double precision array of dimensions (lda, kb), where kb is k when
   *        trans == 'N' or 'n', and is n otherwise. When trans == 'N' or 'n',
   *        the leading n x k part of array B must contain the matrix B,
   *        otherwise the leading k x n part of the array must contain the matrix
   *        B.
   * ldb    leading dimension of N. When trans == 'N' or 'n' then ldb must be at
   *        least max(1, n). Otherwise ldb must be at least max(1, k).
   * beta   double precision scalar multiplier applied to C. If beta is 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. Must be at least max(1, n).
   *
   * Output
   * ------
   * C      updated according to alpha*A*transpose(B) + alpha*B*transpose(A) +
   *        beta*C or alpha*transpose(A)*B + alpha*transpose(B)*A + beta*C
  *
    * Reference:   http://www.netlib.org/blas/dsyr2k.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>
    */

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