ungqr_batch (Buffer Strided Version)

oneMKL - Data Parallel C++ Developer Reference

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ID 772045

Date 10/31/2024

Version

Public

Visible to Intel only — GUID: GUID-612964F7-3DB3-45D3-94B7-8EA7FA3DACC8

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ungqr_batch (Buffer Strided Version)

Generates the complex unitary matrices Q_i of the batch of QR factorizations formed by geqrf_batch function (Buffer stride version). This routine belongs to the oneapi::mkl::lapack namespace.

Description
API

Description

The routine generates the wholes or parts of m-by-m unitary matrix Q_i of the QR factorization formed by the geqrf_batch (Buffer Strided Version) function.

Usually Q_i is determined from the QR factorization of an m by p matrix A_i with m ≥ p. To compute the whole matrices Q_i, use:

ungqr_batch(queue, m, m, p, a, ...)

To compute the leading p columns of Q_i (which form an orthonormal basis in the space spanned by the columns of A_i):

ungqr_batch(queue, m, p, p, a, ...)

To compute the matrix Q_i^k of the QR factorization of the leading k columns of the matrices A_i:

ungqr_batch(queue, m, m, k, a, ...)

To compute the leading k columns of Q_i^k (which form an orthonormal basis in the space spanned by the leading k columns of the matrices A_i):

ungqr_batch(queue, m, k, k, a, ...)

API

Syntax

namespace oneapi::mkl::lapack {
  void ungqr_batch(sycl::queue &queue,
  int64_t m,
  int64_t n,
  int64_t k,
  sycl::buffer<T> &a,
  int64_t lda,
  int64_t stride_a,
  sycl::buffer<T> &tau,
  int64_t stride_tau,
  int64_t batch_size,
  sycl::buffer<T> &scratchpad,
  int64_t scratchpad_size)
}

This function supports the following precisions and devices:

T	Devices supported
`std::complex<float>`	CPU and GPU*
`std::complex<double>`	CPU and GPU*

*Interface support only; all computations are performed on the CPU.

Input Parameters

queue: Device queue where calculations will be performed.
m: The number of rows in the matrices A_i (m ≥ 0).
n: The number of columns in the matrices A_i (n ≥ 0).
k: the number of elementary reflectors whose product defines the matrices Q_i (0 ≤ k ≤ n) .
a: Array resulting after a call to geqrf_batch (Buffer Strided Version).
lda: The leading dimension of A_i (lda ≥ max(1,m)).
stride_a: The stride between the beginnings of matrices A_i inside the batch array a (stride_a ≥ max(1, lda * n)).
tau: Array resulting after a call to geqrf_batch (Buffer Strided Version).
stride_tau: The stride between the beginnings of arrays tau_i inside the array tau (stride_tau ≥ max(1, min(m,n))).
batch_size: The number of problems in a batch (batch_size ≥ 0).
scratchpad: Scratchpad memory to be used by routine for storing intermediate results.
scratchpad_size: Size of scratchpad memory as a number of floating point elements of type T. Size should not be less than the value returned by ungqr_batch_scratchpad_size (Strided Version).

Output Parameters

a: Array data is overwritten by a batch of n leading columns of the m-by-m unitary matrices Q_i.

Exceptions

Exception	Description
`mkl::lapack::batch_exception`	This exception is thrown when problems occur during calculations. You can obtain the info code of the problem using the info() method of the exception object: If `info = -n`, the `n`-th parameter had an illegal value. If `info` equals the value passed as scratchpad size, and detail() returns non-zero, then the passed scratchpad is of insufficient size, and the required size should be not less then value returned by the detail() method of the exception object.

Exception

Description

mkl::lapack::batch_exception

This exception is thrown when problems occur during calculations. You can obtain the info code of the problem using the info() method of the exception object:

If info = -n, the n-th parameter had an illegal value.

If info equals the value passed as scratchpad size, and detail() returns non-zero, then the passed scratchpad is of insufficient size, and the required size should be not less then value returned by the detail() method of the exception object.

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oneMKL - Data Parallel C++ Developer Reference

ungqr_batch (Buffer Strided Version)

Description

API