ungbr_scratchpad_size
Contents
ungbr_scratchpad_size#
Computes size of scratchpad memory required for ungbr function.
Description
ungbr_scratchpad_size
supports the following precisions.
T
std::complex<float>
std::complex<double>
Computes the number of elements of type \(T\) the scratchpad memory to be passed to ungbr function should be able to hold. Calls to this routine must specify the template parameter explicitly.
ungbr_scratchpad_size#
Syntax
namespace oneapi::mkl::lapack {
template <typename T>
std::int64_t ungbr_scratchpad_size(cl::sycl::queue &queue, oneapi::mkl::generate gen, std::int64_t m, std::int64_t n, std::int64_t k, std::int64_t lda, std::int64_t &scratchpad_size)
}
Input Parameters
- queue
Device queue where calculations by ungbr function will be performed.
- gen
Must be
generate::q
orgenerate::p
.If
gen = generate::q
, the routine generates the matrix \(Q\).If
gen = generate::p
, the routine generates the matrix \(P^{T}\).- m
The number of rows in the matrix \(Q\) or \(P^{T}\) to be returned \((0 \le m)\).
If
gen = generate::q
, \(m \ge n \ge \min(m, k)\).If
gen = generate::p
, \(n \ge m \ge \min(n, k)\).- n
The number of columns in the matrix \(Q\) or \(P^{T}\) to be returned \((0 \le n)\). See m for constraints.
- k
If
gen = generate::q
, the number of columns in the original \(m \times k\) matrix reduced by gebrd.If
gen = generate::p
, the number of rows in the original \(k \times n\) matrix reduced by gebrd.- lda
The leading dimension of
a
.
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::unsupported_device
oneapi::mkl::lapack::invalid_argument
Exception is thrown in case of incorrect supplied argument value. Position of wrong argument can be determined by info() method of exception object.
Return Value
The number of elements of type T
the scratchpad memory to be passed to ungbr function should be able to hold.
Parent topic: LAPACK Singular Value and Eigenvalue Problem Routines