Visible to Intel only — GUID: GUID-8F1494B7-0132-4064-999B-288C19B5A2BD
Visible to Intel only — GUID: GUID-8F1494B7-0132-4064-999B-288C19B5A2BD
hbmv
Computes a matrix-vector product using a hermitian band matrix.
Description
The hbmv routines compute a scalar-matrix-vector product and add the result to a scalar-vector product, with a hermitian band matrix. The operation is defined as:
where:
alpha and beta are scalars
A is n x n hermitian band matrix, with k super-diagonals
x and y are vectors of length n
hbmv supports the following precisions:
T |
---|
std::complex<float> |
std::complex<double> |
hbmv (Buffer Version)
Syntax
namespace oneapi::mkl::blas::column_major { void hbmv(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 hbmv(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.
- 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.
hbmv (USM Version)
Syntax
namespace oneapi::mkl::blas::column_major { sycl::event hbmv(sycl::queue &queue, oneapi::mkl::uplo upper_lower, std::int64_t n, std::int64_t k, 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 hbmv(sycl::queue &queue, oneapi::mkl::uplo upper_lower, std::int64_t n, std::int64_t k, 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.
- 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
-
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.
- 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.