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sbmv

sbmv#

Computes a matrix-vector product with a symmetric band matrix.

Description

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

\[y \leftarrow alpha*A*x + beta*y\]

where:

alpha and beta are scalars,

A is an n-by-n symmetric matrix with k super-diagonals,

x and y are vectors of length n.

sbmv supports the following precisions.

T

float

double

sbmv (Buffer Version)#

Syntax

namespace oneapi::mkl::blas::column_major {
    void sbmv(sycl::queue &queue,
              onemkl::uplo upper_lower,
              std::int64_t n,
              std::int64_t k,
              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 sbmv(sycl::queue &queue,
              onemkl::uplo upper_lower,
              std::int64_t n,
              std::int64_t k,
              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.

k

Number of super-diagonals of the matrix 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 Storage for more details.

lda

Leading dimension of matrix A. Must be at least (k + 1), and positive.

x

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

incy

Stride of vector y.

Output Parameters

y

Buffer holding the updated vector y.

sbmv (USM Version)#

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event sbmv(sycl::queue &queue,
                     onemkl::uplo upper_lower,
                     std::int64_t n,
                     std::int64_t k,
                     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 sbmv(sycl::queue &queue,
                     onemkl::uplo upper_lower,
                     std::int64_t n,
                     std::int64_t k,
                     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.

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.

k

Number of super-diagonals of the matrix 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 Storage for more details.

lda

Leading dimension of matrix A. Must be at least (k + 1), 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 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 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

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