hemv¶

Computes a matrix-vector product using a Hermitian matrix.

hemv supports the following precisions.

T

std::complex<float>

std::complex<double>

Description

The hemv routines compute a scalar-matrix-vector product and add the result to a scalar-vector product, with a Hermitian 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,

x and y are vectors of length n.

hemv (Buffer Version)¶

Syntax

void onemkl::blas::hemv(sycl::queue &queue, onemkl::uplo upper_lower, std::int64_t n, T alpha, sycl::buffer<T, 1> &a, std::int64_t lda, 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 lda*n. See Matrix and Vector Storage for more details.
lda: Leading dimension of matrix A. Must be at least m, and positive.
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.

hemv (USM Version)¶

Syntax

sycl::event onemkl::blas::hemv(sycl::queue &queue, onemkl::uplo upper_lower, std::int64_t n, T alpha, const T *a, std::int64_t lda, 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 lda*n. See Matrix and Vector Storage for more details.
lda: Leading dimension of matrix A. Must be at least m, and positive.
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