Developer Reference for Intel® oneAPI Math Kernel Library - C

Developer Reference

  • 2021.1
  • 12/04/2020
  • Public Content
Contents

cblas_?gemm

Computes a matrix-matrix product with general matrices.

Syntax

void
cblas_sgemm
(
const
CBLAS_LAYOUT
Layout
,
const
CBLAS_TRANSPOSE
transa
,
const
CBLAS_TRANSPOSE
transb
,
const
MKL_INT
m
,
const
MKL_INT
n
,
const
MKL_INT
k
,
const
float
alpha
,
const
float
*a
,
const
MKL_INT
lda
,
const
float
*b
,
const
MKL_INT
ldb
,
const
float
beta
,
float
*c
,
const
MKL_INT
ldc
);
void
cblas_dgemm
(
const
CBLAS_LAYOUT
Layout
,
const
CBLAS_TRANSPOSE
transa
,
const
CBLAS_TRANSPOSE
transb
,
const
MKL_INT
m
,
const
MKL_INT
n
,
const
MKL_INT
k
,
const
double
alpha
,
const
double
*a
,
const
MKL_INT
lda
,
const
double
*b
,
const
MKL_INT
ldb
,
const
double
beta
,
double
*c
,
const
MKL_INT
ldc
);
void
cblas_cgemm
(
const
CBLAS_LAYOUT
Layout
,
const
CBLAS_TRANSPOSE
transa
,
const
CBLAS_TRANSPOSE
transb
,
const
MKL_INT
m
,
const
MKL_INT
n
,
const
MKL_INT
k
,
const
void
*alpha
,
const
void
*a
,
const
MKL_INT
lda
,
const
void
*b
,
const
MKL_INT
ldb
,
const
void
*beta
,
void
*c
,
const
MKL_INT
ldc
);
void
cblas_zgemm
(
const
CBLAS_LAYOUT
Layout
,
const
CBLAS_TRANSPOSE
transa
,
const
CBLAS_TRANSPOSE
transb
,
const
MKL_INT
m
,
const
MKL_INT
n
,
const
MKL_INT
k
,
const
void
*alpha
,
const
void
*a
,
const
MKL_INT
lda
,
const
void
*b
,
const
MKL_INT
ldb
,
const
void
*beta
,
void
*c
,
const
MKL_INT
ldc
);
Include Files
  • mkl.h
Description
The
?gemm
 routines compute a scalar-matrix-matrix product and add the result to a scalar-matrix product, with general matrices. The operation is defined as 
C := alpha*op(A)*op(B) + beta*C
where:
op(
X
)
 is one of
op(
X
) =
X
, or
op(
X
) =
X
T
, or
op(
X
) =
X
H
,
alpha
 and
beta
 are scalars,
A
,
B
 and
C
 are matrices:
op(
A
)
 is an
m
-by-
k
 matrix,
op(
B
)
 is a
k
-by-
n
 matrix,
C
 is an
m
-by-
n
 matrix.
See also:
  • ?gemm
     for the Fortran language interface to this routine
  • ?gemm3m
    , BLAS-like extension routines, that use matrix multiplication for similar matrix-matrix operations
Input Parameters
Layout
Specifies whether two-dimensional array storage is row-major (
CblasRowMajor
) or column-major (
CblasColMajor
).
transa
Specifies the form of
op(
A
)
used in the matrix multiplication:
  • if
    transa
    =
    CblasNoTrans
    , then
    op(
    A
    ) =
    A
    ;
  • if
    transa
    =
    CblasTrans
    , then
    op(
    A
    ) =
    A
    T
    ;
  • if
    transa
    =
    CblasConjTrans
    , then
    op(
    A
    ) =
    A
    H
    .
transb
Specifies the form of
op(
B
)
used in the matrix multiplication:
  • if
    transb
    =
    CblasNoTrans
    , then
    op(
    B
    ) =
    B
    ;
  • if
    transb
    =
    CblasTrans
    , then
    op(
    B
    ) =
    B
    T
    ;
  • if
    transb
    =
    CblasConjTrans
    , then
    op(
    B
    ) =
    B
    H
    .
m
Specifies the number of rows of the matrix
op(
A
)
 and of the matrix
C
. The value of
m
 must be at least zero.
n
Specifies the number of columns of the matrix
op(
B
)
 and the number of columns of the matrix
C
. The value of
n
 must be at least zero.
k
Specifies the number of columns of the matrix
op(
A
)
 and the number of rows of the matrix
op(
B
)
. The value of
k
 must be at least zero.
alpha
Specifies the scalar
alpha
.
a
transa
=
CblasNoTrans
transa
=
CblasTrans
 or
transa
=
CblasConjTrans
Layout
 =
CblasColMajor
Array, size
lda
*
k
.
Before entry, the leading
m
-by-
k
 part of the array
a
 must contain the matrix
A
.
Array, size
lda
*
m
.
Before entry, the leading
k
-by-
m
 part of the array
a
 must contain the matrix
A
.
Layout
 =
CblasRowMajor
Array, size
lda
*
m
.
Before entry, the leading
k
-by-
m
 part of the array
a
 must contain the matrix
A
.
Array, size
lda
*
k
.
Before entry, the leading
m
-by-
k
 part of the array
a
 must contain the matrix
A
.
lda
Specifies the leading dimension of
a
 as declared in the calling (sub)program.
transa
=
CblasNoTrans
transa
=
CblasTrans
 or
transa
=
CblasConjTrans
Layout
 =
CblasColMajor
lda
 must be at least
max(1,
m
)
.
lda
 must be at least
max(1,
k
)
Layout
 =
CblasRowMajor
lda
 must be at least
max(1,
k
)
lda
 must be at least
max(1,
m
)
.
b
transb
=
CblasNoTrans
transb
=
CblasTrans
 or
transb
=
CblasConjTrans
Layout
 =
CblasColMajor
Array, size
ldb
 by
n
. Before entry, the leading
k
-by-
n
 part of the array
b
 must contain the matrix
B
.
Array, size
ldb
 by
k
. Before entry the leading
n
-by-
k
 part of the array
b
 must contain the matrix
B
.
Layout
 =
CblasRowMajor
Array, size
ldb
 by
k
. Before entry the leading
n
-by-
k
 part of the array
b
 must contain the matrix
B
.
Array, size
ldb
 by
n
. Before entry, the leading
k
-by-
n
 part of the array
b
 must contain the matrix
B
.
ldb
Specifies the leading dimension of
b
 as declared in the calling (sub)program.
When
transb
=
CblasNoTrans
 , then
ldb
 must be at least
max(1,
k
)
, otherwise
ldb
 must be at least
max(1,
n
)
.
transb
=
CblasNoTrans
transb
=
CblasTrans
 or
transb
=
CblasConjTrans
Layout
 =
CblasColMajor
ldb
 must be at least
max(1,
k
)
.
ldb
 must be at least
max(1,
n
)
.
Layout
 =
CblasRowMajor
ldb
 must be at least
max(1,
n
)
.
ldb
 must be at least
max(1,
k
)
.
beta
Specifies the scalar
beta
. When
beta
 is equal to zero, then
c
 need not be set on input.
c
Layout
 =
CblasColMajor
Array, size
ldc
 by
n
. Before entry, the leading
m
-by-
n
 part of the array
c
 must contain the matrix
C
, except when
beta
 is equal to zero, in which case
c
 need not be set on entry.
Layout
 =
CblasRowMajor
Array, size
ldc
 by
m
. Before entry, the leading
n
-by-
m
 part of the array
c
 must contain the matrix
C
, except when
beta
 is equal to zero, in which case
c
 need not be set on entry.
ldc
Specifies the leading dimension of
c
 as declared in the calling (sub)program.
Layout
 =
CblasColMajor
ldc
 must be at least
max(1,
m
)
.
Layout
 =
CblasRowMajor
ldc
 must be at least
max(1,
n
)
.
Output Parameters
c
Overwritten by the
m
-by-
n
 matrix
(
alpha
*op(
A
)*op(
B
) +
beta
*
C
)
.

Example

For examples of
routine
 usage, see these code examples in the
Intel® oneAPI Math Kernel Library
 installation directory:
  • cblas_sgemm
    :
    examples\cblas\source\cblas_sgemmx.c
  • cblas_dgemm
    :
    examples\cblas\source\cblas_dgemmx.c
  • cblas_cgemm
    :
    examples\cblas\source\cblas_cgemmx.c
  • cblas_zgemm
    :
    examples\cblas\source\cblas_zgemmx.c

Product and Performance Information

1

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