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

\[y \leftarrow alpha*op(A)*x + beta*y\]

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 an m-by-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>

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

gbmv (Buffer Version)¶

Syntax

namespace oneapi::mkl::blas::column_major {
    void gbmv(sycl::queue &queue,
              onemkl::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(sycl::queue &queue,
              onemkl::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 A. See oneMKL defined datatypes for more details.
m: Number of rows of A. Must be at least zero.
n: Number of columns of A. Must be at least zero.
kl: Number of sub-diagonals of the matrix A. Must be at least zero.
ku: 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 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. The buffer must be of size 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. The buffer must be of size at least (1 + (len - 1)*abs(incy)) where len is this length. See Matrix Storage for more details.
incy: Stride of vector y.

Output Parameters

y: Buffer holding the updated vector y.

Throws

This routine shall throw the following exceptions if the associated condition is detected. An implementation may throw additional implementation-specific exception(s) in case of error conditions not covered here.

oneapi::mkl::invalid_argument

oneapi::mkl::unsupported_device

oneapi::mkl::host_bad_alloc

oneapi::mkl::device_bad_alloc

oneapi::mkl::unimplemented

gbmv (USM Version)¶

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event gbmv(sycl::queue &queue,
                     onemkl::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 sycl::vector_class<sycl::event> &dependencies = {})
}

namespace oneapi::mkl::blas::row_major {
    sycl::event gbmv(sycl::queue &queue,
                     onemkl::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 sycl::vector_class<sycl::event> &dependencies = {})
}

Input Parameters

queue: The queue where the routine should be executed.
trans: Specifies op(A), the transposition operation applied to A. See oneMKL defined datatypes for more details.
m: Number of rows of A. Must be at least zero.
n: Number of columns of A. Must be at least zero.
kl: Number of sub-diagonals of the matrix A. Must be at least zero.
ku: 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 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. The array holding input vector x must be of size 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. The array holding input/output vector y must be of size 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.