syrk

oneMKL - Data Parallel C++ Developer Reference

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ID 772045

Date 11/07/2023

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syrk

Performs a symmetric rank-k update.

Description

The syrk routines perform a rank-k update of a symmetric matrix C by a general matrix A. The operation is defined as:

where:

op(X) is one of op(X) = X or op(X) = X^T
alpha and beta are scalars
C is n x n symmetric matrix,
op(A) is n x k general matrix

syrk supports the following precisions:

T
`float`
`double`
`std::complex<float>`
`std::complex<double>`

syrk (Buffer Version)

Syntax

namespace oneapi::mkl::blas::column_major {
    void syrk(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,
              T beta,
              sycl::buffer<T,1> &c,
              std::int64_t ldc,
              compute_mode mode = compute_mode::unset)
}

namespace oneapi::mkl::blas::row_major {
    void syrk(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,
              T beta,
              sycl::buffer<T,1> &c,
              std::int64_t ldc,
              compute_mode mode = compute_mode::unset)
}

Input Parameters

queue

The queue where the routine should be executed.

upper_lower

Specifies whether matrix C is upper or lower triangular. See Data Types for more details.

trans

Specifies op(A), the transposition operation applied to matrix A. Conjugation is never performed even if trans = transpose::conjtrans. See Data Types for more details.

n

Number of rows and columns of matrix C. Must be at least zero.

k

Number of columns of matrix op(A). Must be at least zero.

alpha

Scaling factor for the rank-k update.

a

Buffer holding input matrix A. See Matrix Storage for more details.

	`trans` = `transpose::nontrans`	`trans` = `transpose::trans` or `trans` = `transpose::conjtrans`
Column major	`A` is `n` x `k` matrix. Size of array `a` must be at least `lda` * `k`	`A` is `k` x `n` matrix. Size of array `a` must be at least `lda` * `n`
Row major	`A` is `n` x `k` matrix. Size of array `a` must be at least `lda` * `n`	`A` is `k` x `n` matrix. Size of array `a` must be at least `lda` * `k`

lda

Leading dimension of matrix A. Must be positive.

	`trans` = `transpose::nontrans`	`trans` = `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`

beta

Scaling factor for matrix C.

c

Buffer holding input/output matrix C. Size of the buffer must be at least ldc * n. See Matrix Storage for more details.

ldc

Leading dimension of matrix C. Must be positive and at least n.

mode

Optional. Compute mode settings. See Compute Modes for more details.

Output Parameters

c: Output buffer overwritten by alpha * op(A) * op(A)^T + beta * C.

syrk (USM Version)

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event syrk(sycl::queue &queue,
                     oneapi::mkl::uplo upper_lower,
                     oneapi::mkl::transpose trans,
                     std::int64_t n,
                     std::int64_t k,
                     oneapi::mkl::value_or_pointer<T> alpha,
                     const T *a,
                     std::int64_t lda,
                     oneapi::mkl::value_or_pointer<T> beta,
                     T *c,
                     std::int64_t ldc,
                     compute_mode mode = compute_mode::unset,
                     const std::vector<sycl::event> &dependencies = {})
}

namespace oneapi::mkl::blas::row_major {
    sycl::event syrk(sycl::queue &queue,
                     oneapi::mkl::uplo upper_lower,
                     oneapi::mkl::transpose trans,
                     std::int64_t n,
                     std::int64_t k,
                     oneapi::mkl::value_or_pointer<T> alpha,
                     const T *a,
                     std::int64_t lda,
                     oneapi::mkl::value_or_pointer<T> beta,
                     T *c,
                     std::int64_t ldc,
                     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 matrix C is upper or lower triangular. See Data Types for more details.

trans

Specifies op(A), the transposition operation applied to matrix A. Conjugation is never performed even if trans = transpose::conjtrans. See Data Types for more details.

n

Number of rows and columns of matrix C. Must be at least zero.

k

Number of columns of matrix op(A). Must be at least zero.

alpha

Scaling factor for the rank-k update. See Scalar Arguments for more information on the value_or_pointer data type.

a

Pointer to input matrix A. See Matrix Storage for more details.

	`trans` = `transpose::nontrans`	`trans` = `transpose::trans` or `trans` = `transpose::conjtrans`
Column major	`A` is `n` x `k` matrix. Size of array `a` must be at least `lda` * `k`	`A` is `k` x `n` matrix. Size of array `a` must be at least `lda` * `n`
Row major	`A` is `n` x `k` matrix. Size of array `a` must be at least `lda` * `n`	`A` is `k` x `n` matrix. Size of array `a` must be at least `lda` * `k`

lda

Leading dimension of matrix A. Must be positive.

	`trans` = `transpose::nontrans`	`trans` = `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`

beta

Scaling factor for matrix C. See Scalar Arguments for more information on the value_or_pointer data type.

c

Pointer to input/output matrix C. Size of the array must be at least ldc * n. See Matrix Storage for more details.

ldc

Leading dimension of matrix C. Must be positive and at least n.

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 matrix, overwritten by alpha * op(A) * op(A)^T + beta * C.

Return Values

Output event to wait on to ensure computation is complete.

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oneMKL - Data Parallel C++ Developer Reference

syrk

Description

syrk (Buffer Version)

syrk (USM Version)