Target implementations

Functions
template<Target target, typename scalar_t >
int64_t	slate::impl::getrf (Matrix< scalar_t > &A, Pivots &pivots, Options const &opts)
	Distributed parallel LU factorization.
template<Target target, typename scalar_t >
int64_t	slate::impl::getrf_nopiv (Matrix< scalar_t > &A, Options const &opts)
	Distributed parallel LU factorization without pivoting.
template<Target target, typename scalar_t >
int64_t	slate::impl::getrf_tntpiv (Matrix< scalar_t > &A, Pivots &pivots, Options const &opts)
	Distributed parallel CALU factorization.
template<Target target, typename scalar_t >
void	slate::impl::getri (Matrix< scalar_t > &A, Pivots &pivots, Options const &opts)
	Distributed parallel inverse of a general matrix.

Detailed Description

Function Documentation

getrf()

template<Target target, typename scalar_t >

int64_t slate::impl::getrf	(	Matrix< scalar_t > &	A,
		Pivots &	pivots,
		Options const &	opts
	)

Distributed parallel LU factorization.

Generic implementation for any target. Panel and lookahead computed on host using Host OpenMP task.

getrf_nopiv()

template<Target target, typename scalar_t >

int64_t slate::impl::getrf_nopiv	(	Matrix< scalar_t > &	A,
		Options const &	opts
	)

Distributed parallel LU factorization without pivoting.

Generic implementation for any target. Panel and lookahead computed on host using Host OpenMP task.

getrf_tntpiv()

template<Target target, typename scalar_t >

int64_t slate::impl::getrf_tntpiv	(	Matrix< scalar_t > &	A,
		Pivots &	pivots,
		Options const &	opts
	)

Distributed parallel CALU factorization.

Generic implementation for any target. Panel and lookahead computed on host using Host OpenMP task.

getri()

template<Target target, typename scalar_t >

void slate::impl::getri	(	Matrix< scalar_t > &	A,
		Pivots &	pivots,
		Options const &	opts
	)

Distributed parallel inverse of a general matrix.

Generic implementation for any target.

todo: This routine is in-place and does not support GPUs. There is another one (out-of-place) that does. What if this one is called with Target::Devices? a) execute on CPUs, b) error out (not supported)?