SLATE 2024.05.31
Software for Linear Algebra Targeting Exascale
|
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. | |
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.
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.
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.
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)?