sbmv

oneMKL - Data Parallel C++ Developer Reference

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ID 772045

Date 3/22/2024

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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.

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oneMKL - Data Parallel C++ Developer Reference

sbmv

Description

sbmv (Buffer Version)

sbmv (USM Version)