gbmv

Intel® oneAPI Math Kernel Library (oneMKL) - Data Parallel C++ Developer Reference

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ID 772045

Date 12/16/2022

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gbmv

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

Description

The gbmv routines compute a scalar-matrix-vector product and add the result to a scalar-vector product, with a general band 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 with kl sub-diagonals and ku super-diagonals
x and y are vectors

gbmv supports the following precisions:

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

gbmv (Buffer Version)

Syntax

namespace oneapi::mkl::blas::column_major {
    void gbmv(queue &queue,
              oneapi::mkl::transpose trans,
              std::int64_t m,
              std::int64_t n,
              std::int64_t kl,
              std::int64_t ku,
              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 gbmv(queue &queue,
              oneapi::mkl::transpose trans,
              std::int64_t m,
              std::int64_t n,
              std::int64_t kl,
              std::int64_t ku,
              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.
kl: Number of sub-diagonals of matrix A. Must be at least zero.
ku: 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 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 at least (kl + ku + 1) and positive.
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: 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.

gbmv (USM Version)

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event gbmv(queue &queue,
                     oneapi::mkl::transpose trans,
                     std::int64_t m,
                     std::int64_t n,
                     std::int64_t kl,
                     std::int64_t ku,
                     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 gbmv(queue &queue,
                     oneapi::mkl::transpose trans,
                     std::int64_t m,
                     std::int64_t n,
                     std::int64_t kl,
                     std::int64_t ku,
                     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.
kl: Number of sub-diagonals of matrix A. Must be at least zero.
ku: Number of super-diagonals 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. See Matrix Storage for more details.
lda: Leading dimension of matrix A. Must be at least (kl + ku + 1) and positive.
x: Pointer to 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 input 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)) where len is this length. 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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