Intel® Math Kernel Library 2018 Developer Reference - C

mkl_sparse_?_dotmv

Computes a sparse matrix-vector product with dot product.

Syntax

sparse_status_t mkl_sparse_s_dotmv (sparse_operation_t operation, float alpha, const sparse_matrix_t A, struct matrix_descr descr, const float *x, float beta, float *y, float *d);

sparse_status_t mkl_sparse_d_dotmv (sparse_operation_t operation, double alpha, const sparse_matrix_t A, struct matrix_descr descr, const double *x, double beta, double *y, double *d);

sparse_status_t mkl_sparse_c_dotmv (sparse_operation_t operation, MKL_Complex8 alpha, const sparse_matrix_t A, struct matrix_descr descr, const MKL_Complex8 *x, MKL_Complex8 beta, MKL_Complex8 *y, float *d);

sparse_status_t mkl_sparse_z_dotmv (sparse_operation_t operation, MKL_Complex16 alpha, const sparse_matrix_t A, struct matrix_descr descr, const MKL_Complex16 *x, MKL_Complex16 beta, MKL_Complex16 *y, double *d);

Include Files

Description

The mkl_sparse_?_dotmv routine computes a sparse matrix-vector product and dot product:

y := alpha*op(A)*x + beta*y
*d := x·y

where alpha and beta are scalars, x and y are vectors, A is an m-by-k matrix, and op(A) performs the operation

Input Parameters

operation

Specifies the operation performed on matrix A.

If operation = SPARSE_OPERATION_NON_TRANSPOSE, op(A) = A.

If operation = SPARSE_OPERATION_TRANSPOSE, op(A) = AT.

If operation = SPARSE_OPERATION_CONJUGATE_TRANSPOSE, op(A) = AH.

alpha

Specifies the scalar alpha.

A

Handle containing sparse matrix in internal data structure.

descr

Structure specifying sparse matrix properties.

sparse_matrix_type_t type - Specifies the type of a sparse matrix:

SPARSE_MATRIX_TYPE_GENERAL

The matrix is processed as is.

SPARSE_MATRIX_TYPE_SYMMETRIC

The matrix is symmetric (only the requested triangle is processed).

SPARSE_MATRIX_TYPE_HERMITIAN

The matrix is Hermitian (only the requested triangle is processed).

SPARSE_MATRIX_TYPE_TRIANGULAR

The matrix is triangular (only the requested triangle is processed).

SPARSE_MATRIX_TYPE_DIAGONAL

The matrix is diagonal (only diagonal elements are processed).

SPARSE_MATRIX_TYPE_BLOCK_TRIANGULAR

The matrix is block-triangular (only requested triangle is processed). (Applies to BSR format only.)

SPARSE_MATRIX_TYPE_BLOCK_DIAGONAL

The matrix is block-diagonal (only diagonal blocks are processed. (Applies to BSR format only.)

sparse_fill_mode_t mode - Specifies the triangular matrix part for symmetric, Hermitian, triangular, and block-triangular matrices:

SPARSE_FILL_MODE_LOWER

The lower triangular matrix part is processed.

SPARSE_FILL_MODE_UPPER

The upper triangular matrix part is processed.

sparse_diag_type_t diag - Specifies diagonal type for non-general matrices:

SPARSE_DIAG_NON_UNIT

Diagonal elements might not be equal to one.

SPARSE_DIAG_UNIT

Diagonal elements are equal to one.
mode

Specifies the triangular matrix part for symmetric, Hermitian, triangular, and block-triangular matrices:

SPARSE_FILL_MODE_LOWER

The lower triangular matrix part is processed.

SPARSE_FILL_MODE_UPPER

The upper triangular matrix part is processed.

diag

Specifies diagonal type for non-general matrices:

SPARSE_DIAG_NON_UNIT

Diagonal elements might not be equal to one.

SPARSE_DIAG_UNIT

Diagonal elements are equal to one.
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 k 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.