JCublasJava/src/main/java/jcuda/jcublas/JCublas.java
public static void cublasDsyr2k(char uplo, char trans, int n, int k, double alpha, Pointer A, int lda, Pointer B, int ldb, double beta, Pointer C, int ldc)
    {
        cublasDsyr2kNative(uplo, trans, n, k, alpha, A, lda, B, ldb, beta, C, ldc);
        checkResultBLAS();
    }
public static void cublasDsyr2k(char uplo, char trans, int n, int k, double alpha, Pointer A, int lda, Pointer B, int ldb, double beta, Pointer C, int ldc)
    {
        cublasDsyr2kNative(uplo, trans, n, k, alpha, A, lda, B, ldb, beta, C, ldc);
        checkResultBLAS();
    }
public static void cublasDsyr2k ( char uplo , char trans , int n , int k , double alpha , Pointer A , int lda , Pointer B , int ldb , double beta , Pointer C , int ldc ) { cublasDsyr2kNative ( uplo , trans , n , k , alpha , A , lda , B , ldb , beta , C , ldc ) ; checkResultBLAS ( ) ; }
<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 )