000901886 001__ 901886
000901886 005__ 20230310131336.0
000901886 020__ $$a978-3-030-75932-2 (print)
000901886 020__ $$a978-3-030-75933-9 (electronic)
000901886 0247_ $$2doi$$a10.1007/978-3-030-75933-9_4
000901886 0247_ $$2Handle$$a2128/28801
000901886 0247_ $$2WOS$$aWOS:000696174000004
000901886 037__ $$aFZJ-2021-03894
000901886 041__ $$aEnglish
000901886 1001_ $$0P:(DE-HGF)0$$aGötschel, Sebastian$$b0
000901886 1112_ $$a9th Workshop on Parallel-in-Time Integration$$conline$$d2020-06-08 - 2020-06-12$$gPinT9$$wonline
000901886 245__ $$aTwelve Ways to Fool the Masses When Giving Parallel-in-Time Results
000901886 260__ $$aCham$$bSpringer International Publishing$$c2021
000901886 29510 $$aParallel-in-Time Integration Methods
000901886 300__ $$a81 - 94
000901886 3367_ $$2ORCID$$aCONFERENCE_PAPER
000901886 3367_ $$033$$2EndNote$$aConference Paper
000901886 3367_ $$2BibTeX$$aINPROCEEDINGS
000901886 3367_ $$2DRIVER$$aconferenceObject
000901886 3367_ $$2DataCite$$aOutput Types/Conference Paper
000901886 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1634307792_15631
000901886 3367_ $$0PUB:(DE-HGF)7$$2PUB:(DE-HGF)$$aContribution to a book$$mcontb
000901886 4900_ $$aSpringer Proceedings in Mathematics & Statistics$$v356
000901886 520__ $$aGetting good speedup—let alone high parallel efficiency—for parallel-in-time (PinT) integration examples can be frustratingly difficult. The high complexity and large number of parameters in PinT methods can easily (and unintentionally) lead to numerical experiments that overestimate the algorithm’s performance. In the tradition of Bailey’s article “Twelve ways to fool the masses when giving performance results on parallel computers”, we discuss and demonstrate pitfalls to avoid when evaluating the performance of PinT methods. Despite being written in a light-hearted tone, this paper is intended to raise awareness that there are many ways to unintentionally fool yourself and others and that by avoiding these fallacies more meaningful PinT performance results can be obtained.
000901886 536__ $$0G:(DE-HGF)POF4-5112$$a5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
000901886 536__ $$0G:(GEPRIS)450829162$$aDFG project 450829162 - Raum-Zeit-parallele Simulation multimodale Energiesystemen (450829162)$$c450829162$$x1
000901886 588__ $$aDataset connected to CrossRef Book Series, Journals: juser.fz-juelich.de
000901886 7001_ $$0P:(DE-HGF)0$$aMinion, Michael$$b1$$eCorresponding author
000901886 7001_ $$0P:(DE-HGF)0$$aRuprecht, Daniel$$b2
000901886 7001_ $$0P:(DE-Juel1)132268$$aSpeck, Robert$$b3
000901886 773__ $$a10.1007/978-3-030-75933-9_4
000901886 8564_ $$uhttps://juser.fz-juelich.de/record/901886/files/12_ways_new.pdf$$yOpenAccess
000901886 909CO $$ooai:juser.fz-juelich.de:901886$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000901886 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132268$$aForschungszentrum Jülich$$b3$$kFZJ
000901886 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5112$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
000901886 9141_ $$y2021
000901886 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000901886 920__ $$lyes
000901886 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
000901886 980__ $$acontrib
000901886 980__ $$aVDB
000901886 980__ $$aUNRESTRICTED
000901886 980__ $$acontb
000901886 980__ $$aI:(DE-Juel1)JSC-20090406
000901886 9801_ $$aFullTexts