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:

$total\_batch\_count = \sum_{i=0}^{group\_count-1}group\_size[i]$

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.

gemv_batch trsm_batch

oneAPI Math Kernel Library (oneMKL) documentation

syrk_batch¶

Description¶

syrk_batch (Buffer Version)¶

Strided API¶

Syntax¶

Input Parameters¶

Output Parameters¶

syrk_batch (USM Version)¶

Group API¶

Syntax¶

Input Parameters¶

Output Parameters¶

Return Values¶

Strided API¶

Syntax¶

Input Parameters¶

Output Parameters¶

Return Values¶