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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) = XT, or op(X) = XH
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,
compute_mode mode = compute_mode::unset)
}
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,
compute_mode mode = compute_mode::unset)
}
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.
- mode
-
Optional. Compute mode settings. See Compute Modes for more details.
Output Parameters
- c
-
Output buffer overwritten by batch_sizesyrk 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) = XT, or op(X) = XH
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:
Syntax
namespace oneapi::mkl::blas::column_major {
sycl::event syrk_batch(sycl::queue &queue,
const oneapi::mkl::uplo *upper_lower,
const oneapi::mkl::transpose *trans,
const std::int64_t *n,
const std::int64_t *k,
const T *alpha,
const T **a,
const std::int64_t *lda,
const T *beta,
T **c,
const std::int64_t *ldc,
std::int64_t group_count,
const std::int64_t *group_size,
compute_mode mode = compute_mode::unset,
const std::vector<sycl::event> &dependencies = {})
}
namespace oneapi::mkl::blas::row_major {
sycl::event syrk_batch(sycl::queue &queue,
const oneapi::mkl::uplo *upper_lower,
const oneapi::mkl::transpose *trans,
const std::int64_t *n,
const std::int64_t *k,
const T *alpha,
const T **a,
const std::int64_t *lda,
const T *beta,
T **c,
const std::int64_t *ldc,
std::int64_t group_count,
const std::int64_t *group_size,
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
-
Array of group_countoneapi::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_countoneapi::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.
- 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
-
Array of pointers to output matrices C overwritten by total_batch_countsyrk 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) = XT, or op(X) = XH
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,
compute_mode mode = compute_mode::unset,
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,
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 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.
- 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 matrices C overwritten by batch_sizesyrk operations of the form alpha * op(A) * op(A)T + beta * C.
Return Values
Output event to wait on to ensure computation is complete.