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tbmv

tbmv#

Computes a matrix-vector product using a triangular band matrix.

Description

The tbmv routines compute a matrix-vector product with a triangular band matrix. The operation is defined as:

\[x \leftarrow op(A)*x\]

where:

op(A) is one of op(A) = A, or op(A) = AT, or op(A) = AH,

A is an n-by-n unit or non-unit, upper or lower triangular band matrix, with (k + 1) diagonals,

x is a vector of length n.

tbmv supports the following precisions.

T

float

double

std::complex<float>

std::complex<double>

tbmv (Buffer Version)#

Syntax

namespace oneapi::mkl::blas::column_major {
    void tbmv(sycl::queue &queue,
              onemkl::uplo upper_lower,
              onemkl::transpose trans,
              onemkl::diag unit_nonunit,
              std::int64_t n,
              std::int64_t k,
              sycl::buffer<T,1> &a,
              std::int64_t lda,
              sycl::buffer<T,1> &x,
              std::int64_t incx)
}

namespace oneapi::mkl::blas::row_major {
    void tbmv(sycl::queue &queue,
              onemkl::uplo upper_lower,
              onemkl::transpose trans,
              onemkl::diag unit_nonunit,
              std::int64_t n,
              std::int64_t k,
              sycl::buffer<T,1> &a,
              std::int64_t lda,
              sycl::buffer<T,1> &x,
              std::int64_t incx)
}

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.

trans

Specifies op(A), the transposition operation applied to A. See oneMKL Defined Datatypes for more details.

unit_nonunit

Specifies whether the matrix A is unit triangular or not. See oneMKL Defined Datatypes for more details.

n

Numbers of rows and columns of A. Must be at least zero.

k

Number of sub/super-diagonals of the matrix A. Must be at least zero.

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.

Output Parameters

x

Buffer holding the updated vector x.

tbmv (USM Version)#

Syntax

namespace oneapi::mkl::blas::column_major {
    sycl::event tbmv(sycl::queue &queue,
                     onemkl::uplo upper_lower,
                     onemkl::transpose trans,
                     onemkl::diag unit_nonunit,
                     std::int64_t n,
                     std::int64_t k,
                     const T *a,
                     std::int64_t lda,
                     T *x,
                     std::int64_t incx,
                     const std::vector<sycl::event> &dependencies = {})
}

namespace oneapi::mkl::blas::row_major {
    sycl::event tbmv(sycl::queue &queue,
                     onemkl::uplo upper_lower,
                     onemkl::transpose trans,
                     onemkl::diag unit_nonunit,
                     std::int64_t n,
                     std::int64_t k,
                     const T *a,
                     std::int64_t lda,
                     T *x,
                     std::int64_t incx,
                     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.

trans

Specifies op(A), the transposition operation applied to A. See oneMKL Defined Datatypes for more details.

unit_nonunit

Specifies whether the matrix A is unit triangular or not. See oneMKL Defined Datatypes for more details.

n

Numbers of rows and columns of A. Must be at least zero.

k

Number of sub/super-diagonals of the matrix A. Must be at least zero.

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.

dependencies

List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies.

Output Parameters

x

Pointer to the updated vector x.

Return Values

Output event to wait on to ensure computation is complete.

Parent topic: BLAS Level 2 Routines

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