Intel® Math Kernel Library 2018 Developer Reference - C
Computes a symmetric Gauss-Zeidel preconditioner with a final matrix-vector multiplication.
sparse_status_t mkl_sparse_s_symgs_mv (const sparse_operation_t operation, const sparse_matrix_t A, struct matrix_descr descr, const float alpha, float *b, float *x, float *y);
sparse_status_t mkl_sparse_d_symgs_mv (const sparse_operation_t operation, const sparse_matrix_t A, struct matrix_descr descr, const double alpha, double *b, double *x, double *y);
sparse_status_t mkl_sparse_c_symgs_mv (const sparse_operation_t operation, const sparse_matrix_t A, struct matrix_descr descr, const MKL_Complex8 alpha, MKL_Complex8 *b, MKL_Complex8 *x, MKL_Complex8 *y);
sparse_status_t mkl_sparse_z_symgs_mv (const sparse_operation_t operation, const sparse_matrix_t A, struct matrix_descr descr, const MKL_Complex16 alpha, MKL_Complex16 *b, MKL_Complex16 *x, MKL_Complex16 *y);
The mkl_sparse_?_symgs_mv routine performs this operation:
x0 := x*alpha; (L + D)*x1 = b - U*x0; (U + D)*x = b - L*x1; y := A*x
where A = L + D + U
Only symmetric matrices are supported, so desc.type must be SPARSE_MATRIX_TYPE_SYMMETRIC.
Specifies the operation performed on input matrix.
SPARSE_OPERATION_NON_TRANSPOSE, op(A) = A.
Transpose (SPARSE_OPERATION_TRANSPOSE) and conjugate transpose (SPARSE_OPERATION_CONJUGATE_TRANSPOSE) are not supported.
Handle containing sparse matrix in internal data structure.
Specifies the scalar alpha.
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. |
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.
Array of size at least m, where m is the number of rows of matrix A.
On entry, the array b must contain the vector b.
Overwritten by the computed vector x.
Array of size at least m, where m is the number of rows of matrix A.
Overwritten by the computed vector y.
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. |