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@INPROCEEDINGS{Baumann:1028863,
author = {Baumann, Thomas and Speck, Robert and Lunet, Thibaut and
Ruprecht, Daniel and Götschel, Sebastian},
title = {{A}daptive {S}tep {S}ize in {SDC} and {W}hat’s {N}ew
{W}ith py{SDC}?},
reportid = {FZJ-2024-04849},
year = {2024},
abstract = {We are transferring well-known concepts from embedded
Runge-Kutta methods to Spectral Deferred Corrections (SDC)
to enable adaptive step size selection.This works by
estimating the local error and updating the step size such
that a set tolerance is matched.The local error is estimated
via a secondary lower-order method and the step size is
updated according to this method's order.Taking a converged
collocation problem, we can generate a secondary solution by
interpolation from all but one collocation node to the
remaining node.Because there is no dependence on how the
collocation problem was solved, advanced SDC approaches such
as inexactness and diagonal preconditioners can be used.We
show with experiments in pySDC that such schemes can
outperform state-of-the-art diagonally implicit Runge-Kutta
methods for partial differential equations in wall-time
measurements.},
month = {Feb},
date = {2024-02-05},
organization = {13th Parallel-in-Time Workshop, Bruges
(Belgium), 5 Feb 2024 - 9 Feb 2024},
subtyp = {After Call},
cin = {JSC},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511) / TIME-X - TIME
parallelisation: for eXascale computing and beyond (955701)},
pid = {G:(DE-HGF)POF4-5112 / G:(EU-Grant)955701},
typ = {PUB:(DE-HGF)6},
doi = {10.34734/FZJ-2024-04849},
url = {https://juser.fz-juelich.de/record/1028863},
}