syr2k#
Performs a symmetric rank-2k update.
Description
The syr2k
routines perform a rank-2k update of an n
x n
symmetric matrix C
by general matrices A
and B
.
If trans
= transpose::nontrans
, the operation is defined as:
where A
and B
are n
x k
matrices.
If trans
= transpose::trans
, the operation is defined as:
where A
and B
are k
x n
matrices.
In both cases:
alpha
and beta
are scalars,
C
is a symmetric matrix and A
,B
are general matrices,
The inner dimension of both matrix multiplications is k
.
syr2k
supports the following precisions:
T
float
double
std::complex<float>
std::complex<double>
syr2k (Buffer Version)#
Syntax
namespace oneapi::mkl::blas::column_major {
void syr2k(sycl::queue &queue,
onemkl::uplo upper_lower,
onemkl::transpose trans,
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 syr2k(sycl::queue &queue,
onemkl::uplo upper_lower,
onemkl::transpose trans,
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
A
’s data is stored in its upper or lower triangle. See oneMKL Defined Datatypes for more details.- trans
Specifies the operation to apply, as described above. Conjugation is never performed, even if
trans
=transpose::conjtrans
.- n
Number of rows and columns in
C
.The value ofn
must be at least zero.- k
Inner dimension of matrix multiplications.The value of
k
must be at least zero.- alpha
Scaling factor for the rank-2k update.
- a
Buffer holding input matrix
A
.trans
=transpose::nontrans
trans
=transpose::trans
ortranspose::conjtrans
Column major
A
is ann
-by-k
matrix so the arraya
must have size at leastlda
*k
.A
is ank
-by-n
matrix so the arraya
must have size at leastlda
*n
Row major
A
is ann
-by-k
matrix so the arraya
must have size at leastlda
*n
.A
is ank
-by-n
matrix so the arraya
must have size at leastlda
*k
.See Matrix Storage for more details.
- lda
The leading dimension of
A
. It must be positive.trans
=transpose::nontrans
trans
=transpose::trans
ortranspose::conjtrans
Column major
lda
must be at leastn
.lda
must be at leastk
.Row major
lda
must be at leastk
.lda
must be at leastn
.- b
Buffer holding input matrix
B
.trans
=transpose::nontrans
trans
=transpose::trans
ortranspose::conjtrans
Column major
B
is ann
-by-k
matrix so the arrayb
must have size at leastldb
*k
B
is ank
-by-n
matrix so the arrayb
must have size at leastldb
*n
.Row major
B
is ann
-by-k
matrix so the arrayb
must have size at leastldb
*n
.B
is ank
-by-n
matrix so the arrayb
must have size at leastldb
*k
.See Matrix Storage for more details.
- ldb
The leading dimension of
B
. It must be positive.trans
=transpose::nontrans
trans
=transpose::trans
ortranspose::conjtrans
Column major
ldb
must be at leastn
.ldb
must be at leastk
.Row major
ldb
must be at leastk
.ldb
must be at leastn
.- beta
Scaling factor for matrix
C
.- c
Buffer holding input/output matrix
C
. Must have size at leastldc
*n
. See Matrix Storage for more details- ldc
Leading dimension of
C
. Must be positive and at leastn
.
Output Parameters
- c
Output buffer, overwritten by the updated
C
matrix.
syr2k (USM Version)#
Syntax
namespace oneapi::mkl::blas::column_major {
sycl::event syr2k(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,
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 syr2k(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,
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
A
’s data is stored in its upper or lower triangle. See oneMKL Defined Datatypes for more details.- trans
Specifies the operation to apply, as described above. Conjugation is never performed, even if
trans
=transpose::conjtrans
.- n
Number of rows and columns in
C
. The value ofn
must be at least zero.- k
Inner dimension of matrix multiplications.The value of
k
must be at least zero.- alpha
Scaling factor for the rank-2k update.
- a
Pointer to input matrix
A
.trans
=transpose::nontrans
trans
=transpose::trans
ortranspose::conjtrans
Column major
A
is ann
-by-k
matrix so the arraya
must have size at leastlda
*k
.A
is ank
-by-n
matrix so the arraya
must have size at leastlda
*n
Row major
A
is ann
-by-k
matrix so the arraya
must have size at leastlda
*n
.A
is ank
-by-n
matrix so the arraya
must have size at leastlda
*k
.See Matrix Storage for more details.
- lda
The leading dimension of
A
. It must be positive.trans
=transpose::nontrans
trans
=transpose::trans
ortranspose::conjtrans
Column major
lda
must be at leastn
.lda
must be at leastk
.Row major
lda
must be at leastk
.lda
must be at leastn
.- b
Pointer to input matrix
B
.trans
=transpose::nontrans
trans
=transpose::trans
ortranspose::conjtrans
Column major
B
is ann
-by-k
matrix so the arrayb
must have size at leastldb
*k
B
is ank
-by-n
matrix so the arrayb
must have size at leastldb
*n
.Row major
B
is ann
-by-k
matrix so the arrayb
must have size at leastldb
*n
.B
is ank
-by-n
matrix so the arrayb
must have size at leastldb
*k
.See Matrix Storage for more details.
- ldb
The leading dimension of
B
. It must be positive.trans
=transpose::nontrans
trans
=transpose::trans
ortranspose::conjtrans
Column major
ldb
must be at leastn
.ldb
must be at leastk
.Row major
ldb
must be at leastk
.ldb
must be at leastn
.- beta
Scaling factor for matrix
C
.- c
Pointer to input/output matrix
C
. Must have size at leastldc
*n
. See Matrix 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 the updated
C
matrix.
Return Values
Output event to wait on to ensure computation is complete.
Parent topic: BLAS Level 3 Routines