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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:
where:
op(X) is one of op(X) = X or op(X) = XH
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 |
Treal |
|---|---|
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,
Treal alpha,
sycl::buffer<T,1> &a,
std::int64_t lda,
Treal beta,
sycl::buffer<T,1> &c,
std::int64_t ldc,
compute_mode mode = compute_mode::unset)
}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,
Treal alpha,
sycl::buffer<T,1> &a,
std::int64_t lda,
Treal beta,
sycl::buffer<T,1> &c,
std::int64_t ldc,
compute_mode mode = compute_mode::unset)
}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
-
Real 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.
- mode
-
Optional. Compute mode settings. See Compute Modes for more details.
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,
oneapi::mkl::value_or_pointer<Treal> alpha,
const T *a,
std::int64_t lda,
oneapi::mkl::value_or_pointer<Treal> beta,
T *c,
std::int64_t ldc,
compute_mode mode = compute_mode::unset,
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,
oneapi::mkl::value_or_pointer<Treal> alpha,
const T *a,
std::int64_t lda,
oneapi::mkl::value_or_pointer<Treal> beta,
T *c,
std::int64_t ldc,
compute_mode mode = compute_mode::unset,
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
-
Real scaling factor for the rank-k update. See Scalar Arguments for more information on the value_or_pointer data type.
- 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. See Scalar Arguments for more information on the value_or_pointer data type.
- 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.
- mode
-
Optional. Compute mode settings. See Compute Modes for more details.
- dependencies
-
Optional. List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.
mode and dependencies may be omitted independently; it is not necessary to specify mode in order to provide 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.