syrk (USM Version)

Performs a symmetric rank-k update.

Syntax

event syrk(queue &exec_queue, uplo upper_lower, 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 vector_class<event> &dependencies = {})

The USM version ofsyrk supports the following precisions and devices:

T

Devices Supported

float

Host, CPU, and GPU

double

Host, CPU, and GPU

std::complex<float>

Host, CPU, and GPU

std::complex<double>

Host, CPU, and GPU

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) = XT ,

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.

Input Parameters

exec_queue

The queue where the routine should be executed.

upper_lower

Specifies whether C’s data is stored in its upper or lower triangle. See Data Types for more details.

trans

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

n

Number of rows in op(A), and 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 (respectively, lda*n) if column (respectively, row) major layout is used to store matrices. Otherwise, A is an k-by-n matrix so the array a must have size at least lda*n (respectively, lda*k) if column (respectively, row) major layout is used to store matrices. See Matrix and Vector Storage for more details.

lda

Leading dimension of A. If matrices are stored using column major layout, lda must be at least n if trans=transpose::nontrans, and at least k otherwise. If matrices are stored using row major layout, lda must be at least k if trans=transpose::nontrans, and at least n otherwise. 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.

dependencies

List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.

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.