Version: 2021.1
Last Updated: 12/04/2020
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mkl_?bsrmv

Computes matrix - vector product of a sparse matrix stored in the BSR format (deprecated).

Syntax

void

mkl_sbsrmv

(

const

char

*transa

const

MKL_INT

const

MKL_INT

const

MKL_INT

*lb

const

float

*alpha

const

char

*matdescra

const

float

*val

const

MKL_INT

*indx

const

MKL_INT

*pntrb

const

MKL_INT

*pntre

const

float

const

float

*beta

float

);

void

mkl_dbsrmv

(

const

char

*transa

const

MKL_INT

const

MKL_INT

const

MKL_INT

*lb

const

double

*alpha

const

char

*matdescra

const

double

*val

const

MKL_INT

*indx

const

MKL_INT

*pntrb

const

MKL_INT

*pntre

const

double

const

double

*beta

double

);

void

mkl_cbsrmv

(

const

char

*transa

const

MKL_INT

const

MKL_INT

const

MKL_INT

*lb

const

MKL_Complex8

*alpha

const

char

*matdescra

const

MKL_Complex8

*val

const

MKL_INT

*indx

const

MKL_INT

*pntrb

const

MKL_INT

*pntre

const

MKL_Complex8

const

MKL_Complex8

*beta

MKL_Complex8

);

void

mkl_zbsrmv

(

const

char

*transa

const

MKL_INT

const

MKL_INT

const

MKL_INT

*lb

const

MKL_Complex16

*alpha

const

char

*matdescra

const

MKL_Complex16

*val

const

MKL_INT

*indx

const

MKL_INT

*pntrb

const

MKL_INT

*pntre

const

MKL_Complex16

const

MKL_Complex16

*beta

MKL_Complex16

);

Include Files

mkl.h

Description

This routine is deprecated. Use mkl_sparse_?_mvfrom the

Intel® oneAPI Math Kernel Library

Inspector-executor Sparse BLAS interface instead.

The

mkl_?bsrmv

routine performs a matrix-vector operation defined as

y := alpha*A*x + beta*y

y := alpha*A^T*x + beta*y,

where:

alpha and beta are scalars,

x and y are vectors,

A is an m-by-k block sparse matrix in the BSR format, A^T is the transpose of A.

This routine supports a BSR format both with one-based indexing and zero-based indexing.

Input Parameters

transa: Specifies the operation.
If
transa
= 'N'
or 'n', then the matrix-vector product is computed as
y := alpha*A*x + beta*y
If
transa
= 'T'
or 't' or 'C' or 'c', then the matrix-vector product is computed as
y := alpha*A^T*x + beta*y
,
m: Number of block rows of the matrix A.
k: Number of block columns of the matrix A.
lb: Size of the block in the matrix A.
alpha: Specifies the scalar alpha.
matdescra: Array of six elements, specifies properties of the matrix used for operation. Only first four array elements are used, their possible values are given in
Table “Possible Values of the Parameter
matdescra
(
descra
)”
. Possible combinations of element values of this parameter are given in
Table “Possible Combinations of Element Values of the Parameter
matdescra
”
.
val: Array containing elements of non-zero blocks of the matrix A. Its length is equal to the number of non-zero blocks in the matrix A multiplied by
lb
*
lb
.
Refer to
values
array description in BSR Format for more details.
indx: For one-based indexing, array containing the column indices plus one for each non-zero block of the matrix A. For zero-based indexing, array containing the column indices for each non-zero block of the matrix A.
Its length is equal to the number of non-zero blocks in the matrix A.
Refer to
columns
array description in BSR Format for more details.
pntrb: Array of length
m
.
This array contains row indices, such that
pntrb
[i] -
pntrb
[0]
is the first index of block row i in the array
indx
Refer to
pointerB
array description in BSR Format for more details.
pntre: Array of length
m
.
For zero-based indexing this array contains row indices, such that
pntre
[i] -
pntrb
[0] - 1
is the last index of block row i in the array
indx
.
Refer to
pointerE
array description in BSR Format for more details.
x: Array, size at least
(
k
*
lb
)
if
transa
= 'N'
or 'n', and at least
(
m
*
lb
)
otherwise. On entry, the array
x
must contain the vector x.
beta: Specifies the scalar beta.
y: Array, size at least
(
m
*
lb
)
if
transa
= 'N'
or 'n', and at least
(
k
*
lb
)
otherwise. On entry, the array
y
must contain the vector y.

Output Parameters

y: Overwritten by the updated vector y.

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

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