Intel® Math Kernel Library 2019 Developer Reference - C
Computes the symmetric product of three sparse matrices and stores the result as a dense matrix.
sparse_status_t mkl_sparse_s_syprd (const sparse_operation_t op , const sparse_matrix_t A, float *B, const sparse_layout_t layoutB, const MKL_INT ldb, float alpha, , 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, float *B, const sparse_layout_t layoutB, const MKL_INT ldb, float alpha, , float beta, float *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, float *B, const sparse_layout_t layoutB, const MKL_INT ldb, float alpha, , float beta, float *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, float *B, const sparse_layout_t layoutB, const MKL_INT ldb, float alpha, , float beta, float *C, const sparse_layout_t layoutC, const MKL_INT ldc);
The mkl_sparse_?_syprd routine performs a multiplication of three sparse matrices that results in a symmetric or Hermitian matrix, C.
C:=alpha*A*B*opA(A) + beta*Cor
C:=alpha*opA(A)*B*A + beta*Cdepending on the input operation variable.
A is a sparse matrix with a general structure. B, and C are dense and symmetric (or Hermitian) matrices. opA(*) is the transpose (real precision) or conjugate transpose (complex precision) operator.
This routine is not supported for sparse matrices in COO or CSC formats. It supports only CSR and BSR formats. In addition, this routine supports only the sorted CSR and sorted BSR formats for the input matrix. If the data is unsorted, call the mkl_sparse_order routine before either mkl_sparse_sypr or mkl_sparse_?_syprd.
operation |
Specifies operation on the input sparse matrices.
|
||||||
A |
Handle containing a sparse matrix in the internal data structure. |
||||||
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.
|
||||||
ldb |
Leading dimension of matrix B. |
||||||
alpha |
Scalar parameter. |
||||||
beta |
Scalar parameter. NoteSince the upper triangular part of matrix C is the only portion that is processed, set real values of alpha and beta in the complex case to obtain the Hermitian matrix. |
||||||
denselayoutC |
Structure that describes the storage scheme for the dense matrix.
|
||||||
ldc |
Leading dimension of matrix C. |
C |
Handle containing the resulting dense matrix. Only the upper-triangular part of the matrix is computed. |
The function returns a value indicating whether the operation was successful, or the reason why it failed.
SPARSE_STATUS_SUCCESS |
The operation was successful. |
SPARSE_STATUS_NOT_INITIALIZED |
The routine encountered an empty handle or matrix array. |
SPARSE_STATUS_ALLOC_FAILED |
The internal memory allocation failed. |
SPARSE_STATUS_INVALID_VALUE |
The input parameters contain an invalid value. |
SPARSE_STATUS_EXECUTION_FAILED |
The execution failed. |
SPARSE_STATUS_INTERNAL_ERROR |
An error occurred in the implementation of the algorithm. |
SPARSE_STATUS_NOT_SUPPORTED |
The requested operation is not supported. |