syrk (USM Version)¶
Performs a symmetric rank-k update.
Description¶
The syrk
routines perform a rank-k update of a symmetric matrix C
by a general matrix A
. The operation is defined as:
where:
op(
X
) is one of op(X
) =X
or op(X
) =X
T,alpha
andbeta
are scalars,C
is a symmetric matrix andA
is a general matrix.
Here op(A
) is n
-by-k
, and C
is n
-by-n
.
API¶
Syntax¶
namespace oneapi::mkl::blas::column_major {
sycl::event syrk(sycl::queue &queue,
onemkl::uplo upper_lower,
onemkl::transpose trans,
std::int64_t n,
std::int64_t k,
T alpha,
const T* a,
std::int64_t lda,
T beta,
T* c,
std::int64_t ldc,
const sycl::vector_class<sycl::event> &dependencies = {})
}
namespace oneapi::mkl::blas::row_major {
sycl::event syrk(sycl::queue &queue,
onemkl::uplo upper_lower,
onemkl::transpose trans,
std::int64_t n,
std::int64_t k,
T alpha,
const T* a,
std::int64_t lda,
T beta,
T* c,
std::int64_t ldc,
const sycl::vector_class<sycl::event> &dependencies = {})
}
The USM version of syrk
supports the following precisions and devices:
T |
Devices Supported |
---|---|
|
Host, CPU, and GPU |
|
Host, CPU, and GPU |
|
Host, CPU, and GPU |
|
Host, CPU, and GPU |
Input Parameters¶
- exec_queue
The queue where the routine should be executed.
- upper_lower
Specifies whether
C
’s data is stored in its upper or lower triangle. See Data Types for more details.- trans
Specifies op(
A
), the transposition operation applied toA
(See Data Types for more details.). Conjugation is never performed, even iftrans
=transpose::conjtrans
.- n
Number of rows in op(
A
), and rows and columns inC
. The value ofn
must be at least zero.- k
Number of columns in op(
A
). The value ofk
must be at least zero.- alpha
Scaling factor for the rank-
k
update.- a
Pointer to input matrix
A
. Iftrans
=transpose::nontrans
,A
is ann
-by-k
matrix so the arraya
must have size at leastlda
*k
(respectively,lda
*n
) if column (respectively, row) major layout is used to store matrices. Otherwise,A
is ank
-by-n
matrix so the arraya
must have size at leastlda
*n
(respectively,lda
*k
) if column (respectively, row) major layout is used to store matrices. See Matrix and Vector Storage for more details.- lda
Leading dimension of
A
. If matrices are stored using column major layout, lda must be at leastn
iftrans
=transpose::nontrans
, and at leastk
otherwise. If matrices are stored using row major layout, lda must be at leastk
iftrans
=transpose::nontrans
, and at leastn
otherwise. Must be positive.- beta
Scaling factor for matrix
C
.- c
Pointer to input/output matrix
C
. Must have size at leastldc
*n
. See Matrix and Vector Storage for more details.- ldc
Leading dimension of
C
. Must be positive and at leastn
.- dependencies
List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.
Output Parameters¶
- c
Pointer to the output matrix, overwritten by
alpha
*op(A
)*op(A
)T +beta
*C
.
Return Values¶
Output event to wait on to ensure computation is complete.