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mkl_sparse_?_symgs_mv

Computes a symmetric Gauss-Seidel preconditioner followed by a matrix-vector multiplication.

Syntax

sparse_status_t
mkl_sparse_s_symgs_mv
(
const
sparse_operation_t
operation
,
const
sparse_matrix_t
A
,
const struct
matrix_descr
descr
,
const
float
alpha
,
const float
*b
,
float
*x
,
float
*y
);
sparse_status_t
mkl_sparse_d_symgs_mv
(
const
sparse_operation_t
operation
,
const
sparse_matrix_t
A
,
const struct
matrix_descr
descr
,
const
double
alpha
,
const double
*b
,
double
*x
,
double
*y
);
sparse_status_t
mkl_sparse_c_symgs_mv
(
const
sparse_operation_t
operation
,
const
sparse_matrix_t
A
,
const struct
matrix_descr
descr
,
const
MKL_Complex8
alpha
,
const 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
,
const struct
matrix_descr
descr
,
const
MKL_Complex16
alpha
,
const MKL_Complex16
*b
,
MKL_Complex16
*x
,
MKL_Complex16
*y
);
Include Files
  • mkl_spblas.h
Description
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
This routine is not supported for sparse matrices in BSR, COO, or CSC formats. It supports only the CSR format. Additionally, only symmetric matrices are supported, so the
desc
.
type
must be
SPARSE_MATRIX_TYPE_SYMMETRIC
.
Input Parameters
operation
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.
A
Handle which contains the sparse matrix
A
.
alpha
Specifies the scalar
alpha
.
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.
x
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
.
b
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
.
Output Parameters
x
Overwritten by the computed vector
x
.
y
Array of size at least
m
, where
m
is the number of rows of matrix
A
.
Overwritten by the computed vector
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.

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.