Developer Reference for Intel® oneAPI Math Kernel Library for C
mkl_sparse_?_dotmv
Computes a sparse matrix-vector product followed by a dot product.
Syntax
sparse_status_t mkl_sparse_s_dotmv ( const sparse_operation_t operation,
const float alpha,
const sparse_matrix_t A,
const struct matrix_descr descr,
const float *x,
const float beta,
float *y,
float *d );sparse_status_t mkl_sparse_d_dotmv ( const sparse_operation_t operation,
const double alpha,
const sparse_matrix_t A,
const struct matrix_descr descr,
const double *x,
const double beta,
double *y,
double *d );sparse_status_t mkl_sparse_c_dotmv ( const sparse_operation_t operation,
const MKL_Complex8 alpha,
const sparse_matrix_t A,
const struct matrix_descr descr,
const MKL_Complex8 *x,
const MKL_Complex8 beta,
MKL_Complex8 *y,
MKL_Complex8 *d );sparse_status_t mkl_sparse_z_dotmv ( const sparse_operation_t operation,
const MKL_Complex16 alpha,
const sparse_matrix_t A,
const struct matrix_descr descr,
const MKL_Complex16 *x,
const MKL_Complex16 beta,
MKL_Complex16 *y,
MKL_Complex16 *d );Include Files
mkl_spblas.h
Description
The mkl_sparse_?_dotmv routine computes a sparse matrix-vector product and dot product:
\[y &\leftarrow \alpha\cdot op(A)\cdot x + \beta\cdot y \\ d &\leftarrow \sum_{i}x_{i}\cdot y_{i} \text{ (real case)} \\ d &\leftarrow \sum_{i}\text{conj}(x_{i})\cdot y_{i} \text{ (complex case)}\]
where \(\alpha\) and \(\beta\) are scalars. \(x\) and \(y\) are vectors. \(A\) is an \(m\) -by- \(k\) matrix. \(\text{conj}\) represents complex conjugation. \(op(A)\) is a matrix modifier.
Available options for \(op(A)\) are \(A\), \(A^{T}\), or \(A^{H}\).
( 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 \(A\):
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:
|
x
If operation = SPARSE_OPERATION_NON_TRANSPOSE, array of size at least \(k\), where \(k\) is the number of columns of matrix \(A\) . Otherwise, array of size at least \(m\), where \(m\) is the number of rows of matrix \(A\) . On entry, the array x must contain the vector x .
beta
Specifies the scalar, \(\beta\) .
y
If operation = SPARSE_OPERATION_NON_TRANSPOSE, array of size at least \(m\) , where \(m\) is the number of rows of matrix \(A\) . Otherwise, array of size at least \(k\) , where \(k\) is the number of columns of matrix \(A\) . On entry, the array y must contain the vector y .
Output Parameters
- y
-
Overwritten by the updated vector y .
d
Overwritten by the dot product of x and y .
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. |