hpmv

Computes a matrix-vector product using a Hermitian packed matrix.

hpmv supports the following precisions.

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

Description

The hpmv routines compute a scalar-matrix-vector product and add the result to a scalar-vector product, with a Hermitian packed matrix. The operation is defined as

y <- alpha*A*x + beta*y

where:

alpha and beta are scalars,

A is an n-by-n Hermitian matrix supplied in packed form,

x and y are vectors of length n.

hpmv (Buffer Version)

Syntax

void onemkl::blas::hpmv(sycl::queue &queue, onemkl::uplo upper_lower, std::int64_t n, T alpha, sycl::buffer<T, 1> &a, sycl::buffer<T, 1> &x, std::int64_t incx, T beta, sycl::buffer<T, 1> &y, std::int64_t incy)

Input Parameters

queue

The queue where the routine should be executed.

upper_lower

Specifies whether A is upper or lower triangular. See oneMKL defined datatypes for more details.

n

Number of rows and columns of A. Must be at least zero.

alpha

Scaling factor for the matrix-vector product.

a

Buffer holding input matrix A. Must have size at least (n*(n+1))/2. See Matrix and Vector Storage for more details.

The imaginary parts of the diagonal elements need not be set and are assumed to be zero.

x

Buffer holding input vector x. The buffer must be of size at least (1 + (n - 1)*abs(incx)). See Matrix and Vector Storage for more details.

incx

Stride of vector x.

beta

Scaling factor for vector y.

y

Buffer holding input/output vector y. The buffer must be of size at least (1 + (n - 1)*abs(incy)). See Matrix and Vector Storage for more details.

incy

Stride of vector y.

Output Parameters

y

Buffer holding the updated vector y.

hpmv (USM Version)

Syntax

sycl::event onemkl::blas::hpmv(sycl::queue &queue, onemkl::uplo upper_lower, std::int64_t n, T alpha, const T *a, const T *x, std::int64_t incx, T beta, T *y, std::int64_t incy, const sycl::vector_class<sycl::event> &dependencies = {})

Input Parameters

queue

The queue where the routine should be executed.

upper_lower

Specifies whether A is upper or lower triangular. See oneMKL defined datatypes for more details.

n

Number of rows and columns of A. Must be at least zero.

alpha

Scaling factor for the matrix-vector product.

a

Pointer to input matrix A. The array holding input matrix A must have size at least (n*(n+1))/2. See Matrix and Vector Storage for more details.

The imaginary parts of the diagonal elements need not be set and are assumed to be zero.

x

Pointer to input vector x. The array holding input vector x must be of size at least (1 + (n - 1)*abs(incx)). See Matrix and Vector Storage for more details.

incx

Stride of vector x.

beta

Scaling factor for vector y.

y

Pointer to input/output vector y. The array holding input/output vector y must be of size at least (1 + (n - 1)*abs(incy)). See Matrix and Vector Storage for more details.

incy

Stride of vector y.

dependencies

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

Output Parameters

y

Pointer to the updated vector y.

Return Values

Output event to wait on to ensure computation is complete.

Parent topic: BLAS Level 2 Routines