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

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

Syntax

void

mkl_scsrmm

(

const

char

*transa

const

MKL_INT

const

MKL_INT

const

MKL_INT

const

float

*alpha

const

char

*matdescra

const

float

*val

const

MKL_INT

*indx

const

MKL_INT

*pntrb

const

MKL_INT

*pntre

const

float

const

MKL_INT

*ldb

const

float

*beta

float

const

MKL_INT

*ldc

);

void

mkl_dcsrmm

(

const

char

*transa

const

MKL_INT

const

MKL_INT

const

MKL_INT

const

double

*alpha

const

char

*matdescra

const

double

*val

const

MKL_INT

*indx

const

MKL_INT

*pntrb

const

MKL_INT

*pntre

const

double

const

MKL_INT

*ldb

const

double

*beta

double

const

MKL_INT

*ldc

);

void

mkl_ccsrmm

(

const

char

*transa

const

MKL_INT

const

MKL_INT

const

MKL_INT

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_INT

*ldb

const

MKL_Complex8

*beta

MKL_Complex8

const

MKL_INT

*ldc

);

void

mkl_zcsrmm

(

const

char

*transa

const

MKL_INT

const

MKL_INT

const

MKL_INT

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_INT

*ldb

const

MKL_Complex16

*beta

MKL_Complex16

const

MKL_INT

*ldc

);

Include Files

mkl.h

Description

This routine is deprecated. Use Use mkl_sparse_?_mmfrom the

Intel® oneAPI Math Kernel Library

Inspector-executor Sparse BLAS interface instead.

The

mkl_?csrmm

routine performs a matrix-matrix operation defined as

C := alpha*A*B + beta*C

C := alpha*A^T*B + beta*C

C := alpha*A^H*B + beta*C,

where:

alpha and beta are scalars,

B and C are dense matrices, A is an m-by-k sparse matrix in compressed sparse row (CSR) format, A^T is the transpose of A, and A^H is the conjugate transpose of A.

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

Input Parameters

transa: Specifies the operation.
If
transa
= 'N'
or 'n', then
C := alpha*A*B + beta*C
,
If
transa
= 'T'
or 't', then
C := alpha*A^T*B + beta*C
,
If
transa
=
'C' or 'c', then
C := alpha*A^H*B + beta*C
.
m: Number of rows of the matrix A.
n: Number of columns of the matrix C.
k: Number of columns of 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 non-zero elements of the matrix A.
For zero-based indexing its length is
pntre
[
m
—1] -
pntrb
[0]
.
Refer to
values
array description in CSR Format for more details.
indx: For one-based indexing, array containing the column indices plus one for each non-zero element of the matrix A.
For zero-based indexing, array containing the column indices for each non-zero element of the matrix A.
Its length is equal to length of the
val
array.
Refer to
columns
array description in CSR 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 row I in the arrays
val
and
indx
.
Refer to
pointerb
array description in CSR Format for more details.
pntre: Array of length
m
.
This array contains row indices, such that
pntre
[I] -
pntrb
[0] - 1
is the last index of row I in the arrays
val
and
indx
.
Refer to
pointerE
array description in CSR Format for more details.
b: Array, size
ldb
by at least
n
for non-transposed matrix A and at least
m
for transposed for one-based indexing, and (at least
k
for non-transposed matrix A and at least
m
for transposed,
ldb
) for zero-based indexing.
On entry with
transa=
'N'
or 'n', the leading
k
-by-
n
part of the array
b
must contain the matrix B, otherwise the leading
m
-by-
n
part of the array
b
must contain the matrix B.
ldb: Specifies the leading dimension of
b
for one-based indexing, and the second dimension of
b
for zero-based indexing, as declared in the calling (sub)program.
beta: Specifies the scalar beta.
c: Array, size
ldc
by
n
for one-based indexing, and
(
m
,
ldc
)
for zero-based indexing.
On entry, the leading
m
-by-
n
part of the array
c
must contain the matrix C, otherwise the leading
k
-by-
n
part of the array
c
must contain the matrix C.
ldc: Specifies the leading dimension of
c
for one-based indexing, and the second dimension of
c
for zero-based indexing, as declared in the calling (sub)program.

Output Parameters

c: Overwritten by the matrix
(alpha*A*B + beta* C)
,
(alpha*A^T*B + beta*C)
, or
(alpha*A^H*B + beta*C)
.

In This Topic

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