sbmv

oneMKL - Data Parallel C++ Developer Reference

Download PDF

ID 772045

Date 6/24/2024

Version

Public

A newer version of this document is available. Customers should click here to go to the newest version.

Visible to Intel only — GUID: GUID-54FBA04F-4B51-4A12-9938-63DDF804EAC2

View Details

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:

where:

alpha and beta are scalars
A is n x 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,
              oneapi::mkl::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,
              oneapi::mkl::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 matrix A is upper or lower triangular. See Data Types for more details.
n: Number of rows and columns of matrix A. Must be at least zero.
k: Number of super-diagonals 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. 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. Size of the buffer must be at least (1 + (n - 1)*abs(incx)). See Matrix Storage for more details.
incx: Stride of vector x. Must not be zero.
beta: Scaling factor for vector y. If beta = 0, vector y does not need to be initialized before calling sbmv.
y: Buffer holding input/output vector y. Size of the buffer must be at least (1 + (n - 1)*abs(incy)). See Matrix Storage for more details.
incy: Stride of vector y. Must not be zero.

Output Parameters

y: Buffer holding updated vector y.

sbmv (USM Version)

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event sbmv(sycl::queue &queue,
                     oneapi::mkl::uplo upper_lower,
                     std::int64_t n,
                     std::int64_t k,
                     oneapi::mkl::value_or_pointer<T> alpha,
                     const T *a,
                     std::int64_t lda,
                     const T *x,
                     std::int64_t incx,
                     oneapi::mkl::value_or_pointer<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,
                     oneapi::mkl::uplo upper_lower,
                     std::int64_t n,
                     std::int64_t k,
                     oneapi::mkl::value_or_pointer<T> alpha,
                     const T *a,
                     std::int64_t lda,
                     const T *x,
                     std::int64_t incx,
                     oneapi::mkl::value_or_pointer<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 matrix A is upper or lower triangular. See Data Types for more details.
n: Number of rows and columns of matrix A. Must be at least zero.
k: Number of super-diagonals of matrix A. Must be at least zero.
alpha: Scaling factor for the matrix-vector product. See Scalar Arguments for more information on the value_or_pointer data type.
a: Pointer to input matrix A. Size of the array holding input matrix A must be 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. Size of the array holding input vector x must be at least (1 + (n - 1)*abs(incx)). See Matrix Storage for more details.
incx: Stride of vector x. Must not be zero.
beta: Scaling factor for vector y. If beta = 0, vector y does not need to be initialized before calling sbmv. See Scalar Arguments for more information on the value_or_pointer data type.
y: Pointer to input/output vector y. Size of the array holding input/output vector y must be at least (1 + (n - 1)*abs(incy)). See Matrix Storage for more details.
incy: Stride of vector y. Must not be zero.
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.

Select Your Language

Using Intel.com Search

Quick Links

Recent Searches

Advanced Search

Only search in

oneMKL - Data Parallel C++ Developer Reference

sbmv

Description

sbmv (Buffer Version)

sbmv (USM Version)