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

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.