syrk¶

Performs a symmetric rank-k update.

syrk supports the following precisions.

T

float

double

std::complex<float>

std::complex<double>

Description

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

C <- alpha*op(A)*op(A)T + beta*C

where:

op(X) is one of op(X) = X or op(X) = X^T ,

alpha and beta are scalars,

C is a symmetric matrix and Ais a general matrix.

Here op(A) is n-by-k, and C is n-by-n.

syrk (Buffer Version)¶

Syntax

void onemkl::blas::syrk(sycl::queue &queue, onemkl::uplo upper_lower, onemkl::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)¶

Input Parameters

queue: The queue where the routine should be executed.
upper_lower: Specifies whether A’s data is stored in its upper or lower triangle. See oneMKL defined datatypes for more details.
trans: Specifies op(A), the transposition operation applied to A (See oneMKL defined datatypes for more details). Conjugation is never performed, even if trans = transpose::conjtrans.
n: Number of rows and columns in C. The value of n must be at least zero.
k: Number of columns in op(A).The value of k must be at least zero.
alpha: Scaling factor for the rank-k update.
a: Buffer holding input matrix A. If trans = transpose::nontrans, A is an n-by-k matrix so the array a must have size at least lda*k. Otherwise, A is an k-by-n matrix so the array a must have size at least lda*n. See Matrix and Vector Storage for more details.
lda: Leading dimension of A. Must be at least n if A is not transposed, and at least k if A is transposed. Must be positive.
beta: Scaling factor for matrix C.
c: Buffer holding input/output matrix C. Must have size at least ldc*n. See Matrix and Vector Storage for more details.
ldc: Leading dimension of C. Must be positive and at least n.

Output Parameters

Syntax

sycl::event onemkl::blas::syrk(sycl::queue &queue, onemkl::uplo upper_lower, onemkl::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, const sycl::vector_class<sycl::event> &dependencies = {})¶

Input Parameters

queue: The queue where the routine should be executed.
upper_lower: Specifies whether A’s data is stored in its upper or lower triangle. See oneMKL defined datatypes for more details.
trans: Specifies op(A), the transposition operation applied to A (See oneMKL defined datatypes for more details). Conjugation is never performed, even if trans = transpose::conjtrans.
n: Number of rows and columns in C. The value of n must be at least zero.
k: Number of columns in op(A). The value of k must be at least zero.
alpha: Scaling factor for the rank-k update.
a: Pointer to input matrix A. If trans = transpose::nontrans, A is an n-by-k matrix so the array a must have size at least lda*k. Otherwise, A is an k-by-n matrix so the array a must have size at least lda*n. See Matrix and Vector Storage for more details.
lda: Leading dimension of A. Must be at least n if A is not transposed, and at least k if A is transposed. Must be positive.
beta: Scaling factor for matrix C.
c: Pointer to input/output matrix C. Must have size at least ldc*n. See Matrix and Vector Storage for more details.
ldc: Leading dimension of C. Must be positive and at least n.

Output Parameters

c: Pointer to the output matrix, overwritten by alpha*op(A)*op(A)^T + beta*C.

Return Values

Output event to wait on to ensure computation is complete.

Parent topic: BLAS Level 3 Routines