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gemv

Computes a matrix-vector product using a general matrix.

Description

The gemv routines compute a scalar-matrix-vector product and add the result to a scalar-vector product, with a general matrix. The operation is defined as:

where:

• op(A) is one of op(A) = A, or op(A) = A^T, or op(A) = A^H

• alpha and beta are scalars

• A is m x n matrix

• x and y are vectors

gemv supports the following precisions:

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

gemv (Buffer Version)

Syntax

namespace oneapi::mkl::blas::column_major {
    void gemv(sycl::queue &queue,
              oneapi::mkl::transpose trans,
              std::int64_t m,
              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)
}

namespace oneapi::mkl::blas::row_major {
    void gemv(sycl::queue &queue,
              oneapi::mkl::transpose trans,
              std::int64_t m,
              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.

trans

Specifies op(A), the transposition operation applied to matrix A. See Data Types for more details.

m

Number of rows of matrix A. Must be at least zero.

n

Number of columns of matrix A. Must be at least zero.

alpha

Scaling factor for the matrix-vector product.

a

Buffer holding input matrix A. Size of the buffer must be at least lda * n if column major layout is used, or at least lda * m if row major layout is used. See Matrix Storage for more details.

lda

Leading dimension of matrix A. Must be positive and at least m if column major layout is used or at least n if row major layout is used.

x

Buffer holding input vector x. The length len of vector x is n if A is not transposed, and m if A is transposed. Size of the buffer must be at least (1 + (len - 1)*abs(incx)). See Matrix Storage for more details.

incx

Stride of vector x.

beta

The scaling factor for vector y.

y

Buffer holding input/output vector y. The length len of vector y is m, if A is not transposed, and n if A is transposed. Size of the buffer must be at least (1 + (len - 1)*abs(incy)). See Matrix Storage for more details.

incy

Stride of vector y.

Output Parameters

y

Buffer holding updated vector y.

Examples

An example of how to use gemv can be found in the oneMKL installation directory, under:

examples/dpcpp/blas/source/gemv.cpp

gemv (USM Version)

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event gemv(sycl::queue &queue,
                     oneapi::mkl::transpose trans,
                     std::int64_t m,
                     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 std::vector<sycl::event> &dependencies = {})
}

namespace oneapi::mkl::blas::row_major {
    sycl::event gemv(sycl::queue &queue,
                     oneapi::mkl::transpose trans,
                     std::int64_t m,
                     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 std::vector<sycl::event> &dependencies = {})
}

Input Parameters

queue

The queue where the routine should be executed.

trans

Specifies op(A), the transposition operation applied to matrix A. See Data Types for more details.

m

Number of rows of matrix A. Must be at least zero.

n

Number of columns of matrix A. Must be at least zero.

alpha

Scaling factor for the matrix-vector product.

a

Pointer to input matrix A. Size of the array must be at least lda * n if column major layout is used, or at least lda * m if row major layout is used.

lda

Leading dimension of matrix A. Must be positive and at least m if column major layout is used or at least n if row major layout is used.

x

Pointer to the input vector x. The length len of vector x is n if A is not transposed, and m if A is transposed. Size of the array holding vector x must be at least (1 + (len - 1)*abs(incx)). See Matrix Storage for more details.

incx

Stride of vector x.

beta

Scaling factor for vector y.

y

Pointer to input/output vector y. The length len of vector y is m, if A is not transposed, and n if A is transposed. Size of the array holding input/output vector y must be at least (1 + (len - 1)*abs(incy)). See Matrix 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 updated vector y.

Return Values

Output event to wait on to ensure computation is complete.

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