hemm (USM Version)

Computes a matrix-matrix product where one input matrix is Hermitian and one is general.

Syntax

event hemm(queue &exec_queue, side left_right, uplo upper_lower, std::int64_t m, std::int64_t n, T alpha, const T *a, std::int64_t lda, const T *b, std::int64_t ldb, T beta, T *c, std::int64_t ldc, const vector_class<event> &dependencies = {})

The USM version of hemm supports the following precisions and devices:

T

Devices Supported

std::complex<float>

Host, CPU, and GPU

std::complex<double>

Host, CPU, and GPU

Description

The hemm routines compute a scalar-matrix-matrix product and add the result to a scalar-matrix product, where one of the matrices in the multiplication is Hermitian. The argument left_right determines if the Hermitian matrix, A, is on the left of the multiplication (left_right = side::left) or on the right (left_right = side::right). Depending on left_right, the operation is defined as

C <- alpha*A*B + beta*C

or

C <- alpha*B*A + beta*C

where:

alpha and beta are scalars,

A is a Hermitian matrix, either m-by-m or n-by-n matrices,

B and C are m-by-n matrices.

Input Parameters

exec_queue

The queue where the routine should be executed.

left_right

Specifies whether A is on the left side of the multiplication (side::left) or on the right side (side::right). See Data Types for more details.

uplo

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

m

Specifies the number of rows of the matrix B and C.

The value of m must be at least zero.

n

Specifies the number of columns of the matrix B and C.

The value of n must be at least zero.

alpha

Scaling factor for the matrix-matrix product.

a

Pointer to input matrix A. Must have size at least lda*m if A is on the left of the multiplication, or lda*n if A is on the right. See Matrix and Vector Storage for more details.

lda

Leading dimension of A. Must be at least m if A is on the left of the multiplication, or at least n if A is on the right. Must be positive.

b

Pointer to input matrix B. It must have a size of at least ldb*n if column major layout is used to store matrices or at least ldb*m if row major layout is used to store matrices. See Matrix and Vector Storage for more details.

ldb

Leading dimension of B. It must be positive and at least m if column major layout is used to store matrices or at least n if column major layout is used to store matrices.

beta

Scaling factor for matrix C.

c

Pointer to input/output matrix C. It must have a size of at least ldc*n if column major layout is used to store matrices or at least ldc*m if row major layout is used to store matrices. See Matrix and Vector Storage for more details.

ldc

Leading dimension of C. It must be positive and at least m if column major layout is used to store matrices or at least n if column major layout is used to store matrices.

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*A*B + beta*C (left_right = side::left) or alpha*B*A + beta*C (left_right = side::right).

Notes

If beta = 0, matrix C does not need to be initialized before calling hemm.

Return Values

Output event to wait on to ensure computation is complete.

hemm her2k