Developer Reference

Contents

gemmt

Computes a matrix-matrix product with general matrices, but updates only the upper or lower triangular part of the result matrix.

Description

The
gemmt
routines compute a scalar-matrix-matrix product and add the result to the upper or lower part of a scalar-matrix product, with general matrices. The operation is defined as:
LaTex Math image.
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
    n
    x
    k
    , op(
    B
    ) is
    k
    x
    n
    , and
    C
    is
    n
    x
    n
gemmt
supports the following precisions:
T
float
double
std::complex<float>
std::complex<double>

gemmt (Buffer Version)

Syntax
namespace oneapi::mkl::blas::column_major { void gemmt(sycl::queue &queue, oneapi::mkl::uplo upper_lower, oneapi::mkl::transpose transa, oneapi::mkl::transpose transb, std::int64_t n, std::int64_t k, T alpha, sycl::buffer<T,1> &a, std::int64_t lda, sycl::buffer<T,1> &b, std::int64_t ldb, T beta, sycl::buffer<T,1> &c, std::int64_t ldc) }
namespace oneapi::mkl::blas::row_major { void gemmt(sycl::queue &queue, oneapi::mkl::uplo upper_lower, oneapi::mkl::transpose transa, oneapi::mkl::transpose transb, std::int64_t n, std::int64_t k, T alpha, sycl::buffer<T,1> &a, std::int64_t lda, sycl::buffer<T,1> &b, std::int64_t ldb, T beta, sycl::buffer<T,1> &c, std::int64_t ldc) }
Input Parameters
queue
The queue where the routine should be executed.
upper_lower
Specifies whether matrix
C
is upper or lower triangular. See Data Types for more details.
transa
Specifies op(
A
), the transposition operation applied to matrix
A
. See Data Types for more details.
transb
Specifies op(
B
), the transposition operation applied to matrix
B
. See Data Types for more details.
n
Number of rows of matrix op(
A
) and matrix
C
. Must be at least zero.
k
Number of columns of matrix op(
A
) and rows of matrix op(
B
). Must be at least zero.
alpha
Scaling factor for matrix-matrix product.
a
Buffer holding input matrix
A
. See Matrix Storage for more details.
transa
=
transpose::nontrans
transa
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
A
is
n
x
k
matrix. Size of array
a
must be at least
lda
*
k
A
is
k
x
n
matrix. Size of array
a
must be at least
lda
*
n
Row major
A
is
n
x
k
matrix. Size of array
a
must be at least
lda
*
n
A
is
k
x
n
matrix. Size of array
a
must be at least
lda
*
k
lda
Leading dimension of matrix
A
. Must be positive.
transa
=
transpose::nontrans
transa
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
Must be at least
n
Must be at least
k
Row major
Must be at least
k
Must be at least
n
b
Buffer holding input matrix
B
. See Matrix Storage for more details.
transb
=
transpose::nontrans
transb
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
B
is
k
x
n
matrix. Size of array
b
must be at least
ldb
*
n
B
is
n
x
k
matrix. Size of array
b
must be at least
ldb
*
k
Row major
B
is
k
x
n
matrix. Size of array
b
must be at least
ldb
*
k
B
is
n
x
k
matrix. Size of array
b
must be at least
ldb
*
n
ldb
Leading dimension of matrix
B
. Must be positive.
transb
=
transpose::nontrans
transb
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
Must be at least
k
Must be at least
n
Row major
Must be at least
n
Must be at least
k
beta
Scaling factor for matrix
C
.
c
Buffer holding input/output matrix
C
. See Matrix Storage for more details.
Column major
C
is
m
x
n
matrix. Size of array
c
must be at least
ldc
*
n
Row major
C
is
m
x
n
matrix. Size of array
c
must be at least
ldc
*
m
ldc
Leading dimension of matrix
C
. Must be positive.
Column major
Must be at least
m
Row major
Must be at least
n
Output Parameters
c
Output buffer overwritten by upper or lower triangular part of
alpha
* op(
A
)*op(
B
) +
beta
*
C
.
If
beta
= 0, matrix
C
does not need to be initialized before calling
gemmt
.

gemmt (USM Version)

Syntax
namespace oneapi::mkl::blas::column_major { sycl::event gemmt(sycl::queue &queue, oneapi::mkl::uplo upper_lower, oneapi::mkl::transpose transa, oneapi::mkl::transpose transb, std::int64_t n, std::int64_t k, T alpha, const T* a, std::int64_t lda, const T* b, std::int64_t ldb, T beta, T* c, std::int64_t ldc, const std::vector<sycl::event> &dependencies = {}) }
namespace oneapi::mkl::blas::row_major { sycl::event gemmt(sycl::queue &queue, oneapi::mkl::uplo upper_lower, oneapi::mkl::transpose transa, oneapi::mkl::transpose transb, std::int64_t n, std::int64_t k, T alpha, const T* a, std::int64_t lda, const T* b, std::int64_t ldb, T beta, T* c, std::int64_t ldc, const std::vector<sycl::event> &dependencies = {}) }
Input Parameters
queue
The queue where the routine should be executed.
upper_lower
Specifies whether matrix
C
is upper or lower triangular. See Data Types for more details.
transa
Specifies op(
A
), the transposition operation applied to matrix
A
. See Data Types for more details.
transb
Specifies op(
B
), the transposition operation applied to matrix
B
. See Data Types for more details.
n
Number of rows of matrix op(
A
) and matrix
C
. Must be at least zero.
k
Number of columns of matrix op(
A
) and rows of matrix op(
B
). Must be at least zero.
alpha
Scaling factor for matrix-matrix product.
a
Pointer to input matrix
A
. See Matrix Storage for more details.
transa
=
transpose::nontrans
transa
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
A
is
n
x
k
matrix. Size of array
a
must be at least
lda
*
k
A
is
k
x
n
matrix. Size of array
a
must be at least
lda
*
n
Row major
A
is
n
x
k
matrix. Size of array
a
must be at least
lda
*
n
A
is
k
x
n
matrix. Size of array
a
must be at least
lda
*
k
lda
Leading dimension of matrix
A
. Must be positive.
transa
=
transpose::nontrans
transa
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
Must be at least
n
Must be at least
k
Row major
Must be at least
k
Must be at least
n
b
Pointer to input matrix
B
. See Matrix Storage for more details.
transb
=
transpose::nontrans
transb
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
B
is
k
x
n
matrix. Size of array
b
must be at least
ldb
*
n
B
is
n
x
k
matrix. Size of array
b
must be at least
ldb
*
k
Row major
B
is
k
x
n
matrix. Size of array
b
must be at least
ldb
*
k
B
is
n
x
k
matrix. Size of array
b
must be at least
ldb
*
n
ldb
Leading dimension of matrix
B
. Must be positive.
transb
=
transpose::nontrans
transb
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
Must be at least
k
Must be at least
n
Row major
Must be at least
n
Must be at least
k
beta
Scaling factor for matrix
C
.
c
Pointer to input/output matrix
C
. See Matrix Storage for more details.
Column major
C
is
m
x
n
matrix. Size of array
c
must be at least
ldc
*
n
Row major
C
is
m
x
n
matrix. Size of array
c
must be at least
ldc
*
m
ldc
Leading dimension of matrix
C
. Must be positive.
Column major
Must be at least
m
Row major
Must be at least
n
dependencies
List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.
Output Parameters
c
Pointer to output matrix
C
overwritten by upper or lower triangular part of
alpha
* op(
A
)*op(
B
) +
beta
*
C
.
If
beta
= 0, matrix
C
does not need to be initialized before calling
gemmt
.
Return Values
Output event to wait on to ensure computation is complete.

Product and Performance Information

1

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