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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 := alpha*op(A)*x + beta*y d := ∑
i
x
i
*y
i
(real case) d := ∑
i
conj(x
i
)*y
i
(complex case)
where
  • alpha
    and
    beta
    are scalars.
  • x
    and
    y
    are vectors.
  • A
    is an
    m
    -by-
    k
    matrix.
  • conj
    represents complex conjugation.
  • op(
    A
    )
    is a matrix modifier.
Available options for
op
(
A
) are
A
,
A
T
, or
A
H
.
For sparse matrices in the BSR format, the supported combinations of (
indexing
,
block_layout
) are:
  • (
    SPARSE_INDEX_BASE_ZERO
    ,
    SPARSE_LAYOUT_ROW_MAJOR
    )
  • (
    SPARSE_INDEX_BASE_ONE
    ,
    SPARSE_LAYOUT_COLUMN_MAJOR
    )
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
) =
A
T
.
If
operation
=
SPARSE_OPERATION_CONJUGATE_TRANSPOSE
,
op(
A
) =
A
H
.
alpha
Specifies the scalar
alpha
.
A
Handle which contains the sparse matrix
A
.
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
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.

Product and Performance Information

1

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