Developer Reference for Intel® oneAPI Math Kernel Library for Fortran
mkl_sparse_?_mv
Computes a sparse matrix - vector product.
Syntax
stat = mkl_sparse_s_mv ( operation, alpha, A, descr, x, beta, y )
stat = mkl_sparse_d_mv ( operation, alpha, A, descr, x, beta, y )
stat = mkl_sparse_c_mv ( operation, alpha, A, descr, x, beta, y )
stat = mkl_sparse_z_mv ( operation, alpha, A, descr, x, beta, y )Include Files
mkl_spblas.f90
Description
The mkl_sparse_?_mv routine computes a sparse matrix-dense vector product defined as
\[y \leftarrow \alpha\cdot op(A)\cdot x + \beta\cdot y\]
where \(\alpha\) and \(\beta\) are scalars, \(x\) and \(y\) are vectors, and \(A\) is a sparse matrix handle of a matrix with \(m\) rows and \(k\) columns, and \(op\) is a matrix modifier for matrix \(A\) .
Input Parameters
operation
C_INT .
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
C_FLOAT |
for mkl_sparse_s_mv |
C_DOUBLE |
for mkl_sparse_d_mv |
C_FLOAT_COMPLEX |
for mkl_sparse_c_mv |
C_DOUBLE_COMPLEX |
for mkl_sparse_z_mv |
Specifies the scalar, \(\alpha\) .
A
SPARSE_MATRIX_T.
Handle which contains the sparse matrix A .
descr
MATRIX_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:
|
x
C_FLOAT |
for mkl_sparse_s_mv |
C_DOUBLE |
for mkl_sparse_d_mv |
C_FLOAT_COMPLEX |
for mkl_sparse_c_mv |
C_DOUBLE_COMPLEX |
for mkl_sparse_z_mv |
Array of size equal to the number of columns, \(k\) of \(A\) if operation = SPARSE_OPERATION_NON_TRANSPOSE and at least the number of rows, \(m\) of \(A\) otherwise. On entry, the array must contain the vector x .
beta
C_FLOAT |
for mkl_sparse_s_mv |
C_DOUBLE |
for mkl_sparse_d_mv |
C_FLOAT_COMPLEX |
for mkl_sparse_c_mv |
C_DOUBLE_COMPLEX |
for mkl_sparse_z_mv |
Specifies the scalar, \(\beta\) .
y
C_FLOAT |
for mkl_sparse_s_mv |
C_DOUBLE |
for mkl_sparse_d_mv |
C_FLOAT_COMPLEX |
for mkl_sparse_c_mv |
C_DOUBLE_COMPLEX |
for mkl_sparse_z_mv |
Array of size at least \(m\) if operation = SPARSE_OPERATION_NON_TRANSPOSE and at least \(k\) otherwise. On entry, the array y must contain the vector y .
Output Parameters
y
C_FLOAT |
for mkl_sparse_s_mv |
C_DOUBLE |
for mkl_sparse_d_mv |
C_FLOAT_COMPLEX |
for mkl_sparse_c_mv |
C_DOUBLE_COMPLEX |
for mkl_sparse_z_mv |
Overwritten by the updated vector y .
stat
INTEGER
Value indicating whether the operation was successful, and if not, 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. |
Return Values
See Output Parameter stat.