mkl_sparse_?

Developer Reference for Intel® oneAPI Math Kernel Library for C

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ID 766684

Date 4/28/2026

Version

Public

mkl_sparse_?_spmmd

Computes the product of two sparse matrices and stores the result as a dense matrix.

Syntax

sparse_status_t mkl_sparse_s_spmmd ( const sparse_operation_t op,
                                     const sparse_matrix_t A,
                                     const sparse_matrix_t B,
                                     const sparse_layout_t layout,
                                           float *C,
                                     const MKL_INT ldc );

sparse_status_t mkl_sparse_d_spmmd ( const sparse_operation_t op,
                                     const sparse_matrix_t A,
                                     const sparse_matrix_t B,
                                     const sparse_layout_t layout,
                                           double *C,
                                     const MKL_INT ldc );

sparse_status_t mkl_sparse_c_spmmd ( const sparse_operation_t op,
                                     const sparse_matrix_t A,
                                     const sparse_matrix_t B,
                                     const sparse_layout_t layout,
                                           MKL_Complex8 *C,
                                     const MKL_INT ldc );

sparse_status_t mkl_sparse_z_spmmd ( const sparse_operation_t op,
                                     const sparse_matrix_t A,
                                     const sparse_matrix_t B,
                                     const sparse_layout_t layout,
                                           MKL_Complex16 *C,
                                     const MKL_INT ldc );

Include Files

mkl_spblas.h

Description

The mkl_sparse_?_spmmd routine performs a matrix-matrix operation:

\[C \leftarrow op(A)\cdot B\]

where \(A\) and \(B\) are sparse matrices, \(op()\) is a matrix modifier for matrix \(A\) , and \(C\) is a dense matrix.

NOTE:

This routine is not supported for sparse matrices in the COO format. For sparse matrices in BSR format, these combinations of ( indexing, block_layout ) are supported:

( SPARSE_INDEX_BASE_ZERO, SPARSE_LAYOUT_ROW_MAJOR )
( SPARSE_INDEX_BASE_ONE, SPARSE_LAYOUT_COLUMN_MAJOR )

Input Parameters

op

Specifies operation on input matrix \(A\).

`op`	Description
`SPARSE_OPERATION_NON_TRANSPOSE`	`\(op(A) = A\)`
`SPARSE_OPERATION_TRANSPOSE`	`\(op(A) = A^{T}\)`
`SPARSE_OPERATION_CONJUGATE_TRANSPOSE`	`\(op(A) = A^{H}\)`

A

Handle which contains the sparse matrix \(A\) .

B

Handle which contains the sparse matrix \(B\) .

layout

Describes the storage scheme for the dense matrix \(C\):

`SPARSE_LAYOUT_COLUMN_MAJOR`	Storage of elements uses column major layout.
`SPARSE_LAYOUT_ROW_MAJOR`	Storage of elements uses row major layout.

ldc

Leading dimension of matrix \(C\) .

Output Parameters

C

The resulting dense matrix.

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.

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