Developer Reference

Contents

syrk_batch

Computes a group of
syrk
operations.

Description

The
syrk_batch
routines are batched versions of syrk, performing multiple
syrk
operations in a single call. Each
syrk
operation performs a rank-k update with general matrices.
syrk_batch
supports the following precisions:
T
float
double
std::complex<float>
std::complex<double>
syrk_batch (Buffer Version)
Buffer version of
syrk_batch
supports only strided API.
Strided API
Strided API operation is defined as:
for i = 0 … batch_size – 1 A and C are matrices at offset i * stridea and i * stridec in a and c. C = alpha * op(A) * op(A)^T + beta * C end for
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
    is general matrix and
    C
    is symmetric matrix
  • op(
    A
    ) is
    n
    x
    k
    and
    C
    is
    n
    x
    n
For strided API,
a
and
c
buffers contain all the input matrices. The stride between matrices is given by the stride parameters. Total number of matrices in
a
and
c
buffers is given by
batch_size
parameter.
Syntax
namespace oneapi::mkl::blas::column_major { void syrk_batch(sycl::queue &queue, oneapi::mkl::uplo upper_lower, oneapi::mkl::transpose trans, std::int64_t n, std::int64_t k, T alpha, sycl::buffer<T,1> &a, std::int64_t lda, std::int64_t stridea, T beta, sycl::buffer<T,1> &c, std::int64_t ldc, std::int64_t stridec, std::int64_t batch_size) }
namespace oneapi::mkl::blas::row_major { void syrk_batch(sycl::queue &queue, oneapi::mkl::uplo upper_lower, oneapi::mkl::transpose trans, std::int64_t n, std::int64_t k, T alpha, sycl::buffer<T,1> &a, std::int64_t lda, std::int64_t stridea, T beta, sycl::buffer<T,1> &c, std::int64_t ldc, std::int64_t stridec, std::int64_t batch_size) }
Input Parameters
queue
The queue where the routine should be executed.
upper_lower
Specifies whether matrices
C
are upper or lower triangular. See Data Types for more details.
trans
Specifies op(
A
), transposition operation applied to matrices
A
. Conjugation is never performed even if
trans
=
transpose::conjtrans
. See Data Types for more details.
n
Number of rows and columns of matrices
C
. Must be at least zero.
k
Number of columns of matrices op(
A
). Must be at least zero.
alpha
Scaling factor for rank-k update.
a
Buffer holding input matrices
A
. Size of the buffer must be at least
stridea
*
batch_size
.
lda
Leading dimension of matrices
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
stridea
Stride between two consecutive
A
matrices.
transa
=
transpose::nontrans
transa
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
Must be at least
lda
*
k
Must be at least
lda
*
n
Row major
Must be at least
lda
*
n
Must be at least
lda
*
k
beta
Scaling factor for matrices
C
.
c
Buffer holding input/output matrices
C
. Size of the buffer must be at least
stridec
*
batch_size
.
ldc
Leading dimension of matrices
C
. Must be positive and at least
n
.
stridec
Stride between two consecutive
C
matrices. Must be least
ldc
*
n
.
batch_size
Specifies the number of matrix multiply operations to perform.
Output Parameters
c
Output buffer overwritten by
batch_size
syrk
operations of the form
alpha
* op(
A
) * op(
A
)
T
+
beta
*
C
.
syrk_batch (USM Version)
USM version of
syrk_batch
supports group API and strided API.
Group API
Group API operation is defined as:
idx = 0 for i = 0 … group_count – 1 for j = 0 … group_size – 1 A, and C are matrices in a[idx] and c[idx] C = alpha[i] * op(A) * op(A)^T + beta[i] * C idx := idx + 1 end for end for
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
    is general matrix and
    C
    is symmetric matrix
  • op(
    A
    ) is
    n
    x
    k
    and
    C
    is
    n
    x
    n
For group API,
a
and
c
arrays contain the pointers for all the input matrices. The total number of matrices in
a
and
c
are given by:
LaTex Math image.
Syntax
namespace oneapi::mkl::blas::column_major { sycl::event syrk_batch(sycl::queue &queue, oneapi::mkl::uplo *upper_lower, oneapi::mkl::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, std::int64_t group_count, std::int64_t *group_size, const std::vector<sycl::event> &dependencies = {}) }
namespace oneapi::mkl::blas::row_major { sycl::event syrk_batch(sycl::queue &queue, oneapi::mkl::uplo *upper_lower, oneapi::mkl::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, std::int64_t group_count, std::int64_t *group_size, const std::vector<sycl::event> &dependencies = {}) }
Input Parameters
queue
The queue where the routine should be executed.
upper_lower
Array of
group_count
oneapi::mkl::uplo
values.
upper_lower[i]
specifies whether matrices
C
are upper or lower triangular in group
i
. See Data Types for more details.
trans
Array of
group_count
oneapi::mkl::transpose
values.
trans[i]
specifies op(
A
), transposition operation applied to matrices
A
in group
i
. See Data Types for more details.
n
Array of
group_count
integers.
n[i]
specifies number of rows and columns of matrices
C
in group
i
. All entries must be at least zero.
k
Array of
group_count
integers.
k[i]
specifies number of columns of matrices op(
A
) in group
i
. All entries must be at least zero.
alpha
Array of
group_count
scalar elements.
alpha[i]
specifies scaling factor for every rank-k update in group
i
.
a
Array of
total_batch_count
pointers for input matrices
A
. See Matrix Storage for more details.
trans
=
transpose::nontrans
trans
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
Size of array
A[i]
must be at least
lda[i]
*
k[i]
Size of array
A[i]
must be at least
lda[i]
*
n[i]
Row major
Size of array
A[i]
must be at least
lda[i]
*
n[i]
Size of array
A[i]
must be at least
lda[i]
*
k[i]
lda
Array of
group_count
integers.
lda[i]
specifies leading dimension of matrices
A
in group
i
. Must be positive.
trans
=
transpose::nontrans
trans
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
Must be at least
n[i]
.
Must be at least
k[i]
.
Row major
Must be at least
k[i]
.
Must be at least
n[i]
.
beta
Array of
group_count
scalar elements.
beta[i]
specifies scaling factor for matrices
C
in group
i
.
c
Array of
total_batch_count
pointers for input/output matrices
C
. Size of array
C[i]
must be at least
ldc[i]
*
n[i]
. See Matrix Storage for more details.
ldc
Array of
group_count
integers.
ldc[i]
specifies leading dimension of matrices
C
in group
i
. Must be positive.
group_count
Number of groups. Must be at least zero.
group_size
Array of
group_count
integers.
group_size[i]
specifies the number of
syrk
operations in group
i
. Each element in
group_size
must be at least zero.
dependencies
List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.
Output Parameters
c
Array of pointers to output matrices
C
overwritten by
total_batch_count
syrk
operations of the form
alpha
* op(
A
) * op(
A
)
T
+
beta
*
C
.
Return Values
Output event to wait on to ensure computation is complete.
Strided API
Strided API operation is defined as:
for i = 0 … batch_size – 1 A and C are matrices at offset i * stridea and i * stridec in a and c. C = alpha * op(A) * op(A)^T + beta * C end for
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
    is general matrix and
    C
    is symmetric matrix
  • op(
    A
    ) is
    n
    x
    k
    and
    C
    is
    n
    x
    n
For strided API,
a
and
c
arrays contain all the input matrices. The stride between matrices is given by the stride parameters. Total number of matrices in
a
and
c
arrays is given by
batch_size
parameter.
Syntax
namespace oneapi::mkl::blas::column_major { sycl::event syrk_batch(sycl::queue &queue, oneapi::mkl::uplo upper_lower, oneapi::mkl::transpose trans, std::int64_t n, std::int64_t k, T alpha, const T *a, std::int64_t lda, std::int64_t stridea, T beta, T *c, std::int64_t ldc, std::int64_t stridec, std::int64_t batch_size, const std::vector<sycl::event> &dependencies = {}) }
namespace oneapi::mkl::blas::row_major { sycl::event syrk_batch(sycl::queue &queue, oneapi::mkl::uplo upper_lower, oneapi::mkl::transpose trans, std::int64_t n, std::int64_t k, T alpha, const T *a, std::int64_t lda, std::int64_t stridea, T beta, T *c, std::int64_t ldc, std::int64_t stridec, std::int64_t batch_size, const std::vector<sycl::event> &dependencies = {}) }
Input Parameters
queue
The queue where the routine should be executed.
upper_lower
Specifies whether matrices
C
are upper or lower triangular. See Data Types for more details.
trans
Specifies op(
A
), transposition operation applied to matrices
A
. Conjugation is never performed even if
trans
=
transpose::conjtrans
. See Data Types for more details.
n
Number of rows and columns of matrices
C
. Must be at least zero.
k
Number of columns of matrices op(
A
). Must be at least zero.
alpha
Scaling factor for rank-k update.
a
Pointer to input matrices
A
. Size of the array must be at least
stridea
*
batch_size
.
lda
Leading dimension of matrices
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
stridea
Stride between two consecutive
A
matrices.
transa
=
transpose::nontrans
transa
=
transpose::trans
or
trans
=
transpose::conjtrans
Column major
Must be at least
lda
*
k
Must be at least
lda
*
n
Row major
Must be at least
lda
*
n
Must be at least
lda
*
k
beta
Scaling factor for matrices
C
.
c
Pointer to input/output matrices
C
. Size of the array must be at least
stridec
*
batch_size
.
ldc
Leading dimension of matrices
C
. Must be positive and at least
n
.
stridec
Stride between two consecutive
C
matrices. Must be least
ldc
*
n
.
batch_size
Specifies the number of matrix multiply operations to perform.
dependencies
List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.
Output Parameters
c
Pointer to output matrices
C
overwritten by
batch_size
syrk
operations of the form
alpha
* op(
A
) * op(
A
)
T
+
beta
*
C
.
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.