Developer Reference for Intel® oneAPI Math Kernel Library for C
mkl_sparse_?_mm
Computes the product of a sparse matrix and a dense matrix and stores the result as a dense matrix.
Syntax
sparse_status_t mkl_sparse_s_mm ( const sparse_operation_t operation,
const float alpha,
const sparse_matrix_t A,
const struct matrix_descr descr,
const sparse_layout_t layout,
const float *B,
const MKL_INT columns,
const MKL_INT ldb,
const float beta,
float *C,
const MKL_INT ldc );sparse_status_t mkl_sparse_d_mm ( const sparse_operation_t operation,
const double alpha,
const sparse_matrix_t A,
const struct matrix_descr descr,
const sparse_layout_t layout,
const double *B,
const MKL_INT columns,
const MKL_INT ldb,
const double beta,
double *C,
const MKL_INT ldc );sparse_status_t mkl_sparse_c_mm ( const sparse_operation_t operation,
const MKL_Complex8 alpha,
const sparse_matrix_t A,
const struct matrix_descr descr,
const sparse_layout_t layout,
const MKL_Complex8 *B,
const MKL_INT columns,
const MKL_INT ldb,
const MKL_Complex8 beta,
MKL_Complex8 *C,
const MKL_INT ldc );sparse_status_t mkl_sparse_z_mm ( const sparse_operation_t operation,
const MKL_Complex16 alpha,
const sparse_matrix_t A,
const struct matrix_descr descr,
const sparse_layout_t layout,
const MKL_Complex16 *B,
const MKL_INT columns,
const MKL_INT ldb,
const MKL_Complex16 beta,
MKL_Complex16 *C,
const MKL_INT ldc );Include Files
mkl_spblas.h
Description
The mkl_sparse_?_mm routine performs a matrix-matrix operation:
\[C \leftarrow \alpha\cdot op(A)\cdot B + \beta\cdot C\]
where \(\alpha\) and \(\beta\) are scalars, \(A\) is a sparse matrix, \(op()\) is a matrix modifier for matrix \(A\) , and \(B\) and \(C\) are dense matrices.
The mkl_sparse_?_mm and mkl_sparse_?_trsm routines support these configurations:
Column-major dense matrix: layout = SPARSE_LAYOUT_COLUMN_MAJOR |
Row-major dense matrix: layout = SPARSE_LAYOUT_ROW_MAJOR |
|
|---|---|---|
0-based sparse matrix: SPARSE_INDEX_BASE_ZERO |
CSR BSR: general non-transposed matrix multiplication only |
All formats |
1-based sparse matrix: SPARSE_INDEX_BASE_ONE |
All formats |
CSR BSR: general non-transposed matrix multiplication only |
( SPARSE_INDEX_BASE_ZERO, SPARSE_LAYOUT_ROW_MAJOR ) or
( SPARSE_INDEX_BASE_ONE, SPARSE_LAYOUT_COLUMN_MAJOR )
Input Parameters
operation
Specifies operation op() on input matrix:
operation |
Description |
|---|---|
SPARSE_OPERATION_NON_TRANSPOSE |
\(op(A) = A\) |
SPARSE_OPERATION_TRANSPOSE |
\(op(A) = A^{T}\) |
SPARSE_OPERATION_CONJUGATE_TRANSPOSE |
\(op(A) = A^{H}\) |
alpha
Specifies the scalar, \(\alpha\) .
A
Handle which contains the sparse matrix A .
descr
Descriptor specifying sparse matrix properties.
sparse_matrix_type_t type |
Specifies the type of a sparse matrix:
|
sparse_fill_mode_t mode |
Specifies the triangular matrix part for symmetric, Hermitian, triangular, and block-triangular matrices:
|
sparse_diag_type_t diag |
Specifies diagonal type for non-general matrices:
|
layout
Describes the storage scheme for the dense matrix:
SPARSE_LAYOUT_COLUMN_MAJOR |
Storage of elements uses column major layout. |
SPARSE_LAYOUT_ROW_MAJOR |
Storage of elements uses row major layout. |
B
Array of size at least rows * cols where .
layout = SPARSE_LAYOUT_COLUMN_MAJOR |
layout = SPARSE_LAYOUT_ROW_MAJOR |
|
|---|---|---|
rows (B_nrows) |
ldb |
If \(op(A) = A\), then A_ncols If \(op(A) = A^{T}\) or \(A^{H}\), then A_nrows |
cols (B_ncols) |
columns |
ldb |
columns
Number of columns of matrix \(C\) .
ldb
Specifies the leading dimension of matrix \(B\) .
beta
Specifies the scalar, \(\beta\) .
C
Array of size at least rows * cols , where
layout = SPARSE_LAYOUT_COLUMN_MAJOR |
layout = SPARSE_LAYOUT_ROW_MAJOR |
|
|---|---|---|
rows (C_nrows) |
ldc |
If \(op(A) = A\), then A_nrows If \(op(A) = A^{T}\) or \(A^{H}\), then A_ncols |
cols (C_ncols) |
columns |
ldc |
- ldc
-
Specifies the leading dimension of matrix \(C\) .
Output Parameters
C
Overwritten by the updated matrix C .
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. |