Intel® oneAPI Math Kernel Library (oneMKL) - Data Parallel C++ Developer Reference

Developer Reference

Contents

herk

Performs a hermitian rank-k update.

Description

The
herk
 routines compute a rank-k update of a hermitian matrix
C
 by a general matrix
A
. The operation is defined as:
LaTex Math image.
where:
  • op(
    X
    ) is one of op(
    X
    ) =
    X
     or op(
    X
    ) =
    X
    H
  • alpha
     and
    beta
     are real scalars
  • C
     is
    n
     x
    n
     hermitian matrix
  • op(
    A
    ) is
    n
     x
    k
     general matrix
herk
 supports the following precisions:
T
T_real
std::complex<float>
float
std::complex<double>
double

herk (Buffer Version)

Syntax
namespace oneapi::mkl::blas::column_major {
    void herk(sycl::queue &queue,
              oneapi::mkl::uplo upper_lower,
              oneapi::mkl::transpose trans,
              std::int64_t n,
              std::int64_t k,
              T_real alpha,
              sycl::buffer<T,1> &a,
              std::int64_t lda,
              T_real beta,
              sycl::buffer<T,1> &c,
              std::int64_t ldc)
}
namespace oneapi::mkl::blas::row_major {
    void herk(sycl::queue &queue,
              oneapi::mkl::uplo upper_lower,
              oneapi::mkl::transpose trans,
              std::int64_t n,
              std::int64_t k,
              T_real alpha,
              sycl::buffer<T,1> &a,
              std::int64_t lda,
              T_real 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.
trans
Specifies op(
A
), the transposition operation applied to matrix
A
. Supported operations are
transpose::nontrans
 and
transpose::conjtrans
. See Data Types for more details.
n
Number of rows and columns of matrix
C
. Must be at least zero.
k
Number of columns of matrix op(
A
). Must be at least zero.
alpha
Complex scaling factor for the rank-k update.
a
Buffer holding input matrix
A
. See Matrix Storage for more details.
trans
 =
transpose::nontrans
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.
trans
 =
transpose::nontrans
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
beta
Real scaling factor for matrix
C
.
c
Buffer holding input/output matrix
C
. Size of the buffer must be at least
ldc
 *
n
. See Matrix Storage for more details.
ldc
Leading dimension of matrix
C
. Must be positive and at least
n
.
Output Parameters
c
Output buffer overwritten by
alpha
 * op(
A
) * op(
A
)
H
 +
beta
 *
C
. The imaginary parts of the diagonal elements are set to zero.

herk (USM Version)

Syntax
namespace oneapi::mkl::blas::column_major {
    sycl::event herk(sycl::queue &queue,
                     oneapi::mkl::uplo upper_lower,
                     oneapi::mkl::transpose trans,
                     std::int64_t n,
                     std::int64_t k,
                     T_real alpha,
                     const T* a,
                     std::int64_t lda,
                     T_real beta,
                     T* c,
                     std::int64_t ldc,
                     const std::vector<sycl::event> &dependencies = {})
}
namespace oneapi::mkl::blas::row_major {
    sycl::event herk(sycl::queue &queue,
                     oneapi::mkl::uplo upper_lower,
                     oneapi::mkl::transpose trans,
                     std::int64_t n,
                     std::int64_t k,
                     T_real alpha,
                     const T* a,
                     std::int64_t lda,
                     T_real 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.
trans
Specifies op(
A
), the transposition operation applied to matrix
A
. Supported operations are
transpose::nontrans
 and
transpose::conjtrans
. See Data Types for more details.
n
Number of rows and columns of matrix
C
. Must be at least zero.
k
Number of columns of matrix op(
A
). Must be at least zero.
alpha
Complex scaling factor for the rank-k update.
a
Pointer to input matrix
A
. See Matrix Storage for more details.
trans
 =
transpose::nontrans
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.
trans
 =
transpose::nontrans
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
beta
Real scaling factor for matrix
C
.
c
Pointer to input/output matrix
C
. Size of the array must be at least
ldc
 *
n
. See Matrix Storage for more details.
ldc
Leading dimension of matrix
C
. Must be positive and 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 overwritten by
alpha
 * op(
A
) * op(
A
)
H
 +
beta
 *
C
. The imaginary parts of the diagonal elements are set to zero.
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.