Developer Reference for Intel® oneAPI Math Kernel Library for C
mkl_sparse_?_syprd
Computes the symmetric triple product of a sparse matrix and a dense matrix and stores the result as a dense matrix.
Syntax
sparse_status_t mkl_sparse_s_syprd ( const sparse_operation_t op,
const sparse_matrix_t A,
const float *B,
const sparse_layout_t layoutB,
const MKL_INT ldb,
const float alpha,
const float beta,
float *C,
const sparse_layout_t layoutC,
const MKL_INT ldc );
sparse_status_t mkl_sparse_d_syprd ( const sparse_operation_t op ,
const sparse_matrix_t A ,
const double *B ,
const sparse_layout_t layoutB ,
const MKL_INT ldb ,
const double alpha ,
const double beta ,
double *C ,
const sparse_layout_t layoutC ,
const MKL_INT ldc );
sparse_status_t mkl_sparse_c_syprd ( const sparse_operation_t op ,
const sparse_matrix_t A ,
const MKL_Complex8 *B ,
const sparse_layout_t layoutB ,
const MKL_INT ldb ,
const MKL_Complex8 alpha ,
const MKL_Complex8 beta ,
MKL_Complex8 *C ,
const sparse_layout_t layoutC ,
const MKL_INT ldc );
sparse_status_t mkl_sparse_z_syprd ( const sparse_operation_t op ,
const sparse_matrix_t A ,
const MKL_Complex16 *B ,
const sparse_layout_t layoutB ,
const MKL_INT ldb ,
const MKL_Complex16 alpha ,
const MKL_Complex16 beta ,
MKL_Complex16 *C ,
const sparse_layout_t layoutC ,
const MKL_INT ldc );
Include Files
mkl_spblas.h
Description
The mkl_sparse_?_syprd routine performs a multiplication of three sparse matrices that results in a symmetric or Hermitian matrix \(C\).
\[C \leftarrow \alpha \cdot A \cdot B \cdot op(A) + \beta \cdot C\]
or
\[C \leftarrow \alpha \cdot op(A) \cdot B \cdot A + \beta \cdot C\]
depending on the matrix modifier operation . Here \(A\) is a sparse matrix, \(B\) and \(C\) are dense and symmetric (or Hermitian) matrices.
\(op()\) is the transpose (real precision) or conjugate transpose (complex precision) operator.
Input Parameters
op
Specifies operation on the input sparse matrix.
SPARSE_OPERATION_NON_TRANSPOSE |
Non-transpose case.
|
SPARSE_OPERATION_TRANSPOSE |
Transpose case. This is not supported for complex matrices.
|
SPARSE_OPERATION_CONJUGATE_TRANSPOSE |
Conjugate transpose case. This is not supported for real matrices.
|
A
Handle which contains the sparse matrix, A .
B
Input dense matrix. Only the upper triangular part of the matrix is used for computation.
denselayoutB
Structure that describes the storage scheme for the dense matrix.
SPARSE_LAYOUT_COLUMN_MAJOR |
Store elements in a column-major layout. |
SPARSE_LAYOUT_ROW_MAJOR |
Store elements in a row-major layout. |
ldb
Leading dimension of dense matrix \(B\).
alpha
Scalar parameter, \(\alpha\).
beta
Scalar parameter, \(\beta\).
denselayoutC
Structure that describes the storage scheme for the dense matrix \(C\).
SPARSE_LAYOUT_COLUMN_MAJOR |
Store elements in a column-major layout. |
SPARSE_LAYOUT_ROW_MAJOR |
Store elements in a row-major layout. |
ldc
Leading dimension of matrix \(C\).
Output Parameters
C
Handle which contains the resulting dense matrix \(C\). Only the upper-triangular part of the matrix is computed.
Return Values
The function returns a value indicating whether the operation was successful or not, and why.
SPARSE_STATUS_SUCCESS |
The operation was successful. |
SPARSE_STATUS_NOT_INITIALIZED |
The routine encountered an empty handle or matrix array. |
SPARSE_STATUS_ALLOC_FAILED |
Internal memory allocation failed. |
SPARSE_STATUS_INVALID_VALUE |
The input parameters contain an invalid value. |
SPARSE_STATUS_EXECUTION_FAILED |
Execution failed. |
SPARSE_STATUS_INTERNAL_ERROR |
An error in algorithm implementation occurred. |
SPARSE_STATUS_NOT_SUPPORTED |
The requested operation is not supported. |