001018544 001__ 1018544 001018544 005__ 20241218210658.0 001018544 0247_ $$2datacite_doi$$a10.34734/FZJ-2023-04872 001018544 037__ $$aFZJ-2023-04872 001018544 041__ $$aEnglish 001018544 1001_ $$0P:(DE-Juel1)132268$$aSpeck, Robert$$b0$$eCorresponding author$$ufzj 001018544 1112_ $$a12th Pint Workshop$$cHarburg$$d2023-07-19 - 2023-07-19$$gPinT2023$$wGermany 001018544 245__ $$apySDC Tutorial @ PinT12 001018544 260__ $$c2023 001018544 3367_ $$2DRIVER$$alecture 001018544 3367_ $$031$$2EndNote$$aGeneric 001018544 3367_ $$2BibTeX$$aMISC 001018544 3367_ $$0PUB:(DE-HGF)17$$2PUB:(DE-HGF)$$aLecture$$blecture$$mlecture$$s1734522275_24845$$xOther 001018544 3367_ $$2ORCID$$aLECTURE_SPEECH 001018544 3367_ $$2DataCite$$aText 001018544 520__ $$aIn this tutorial we will give an introduction to our Python prototyping framework pySDC, which provides various implementations of spectral deferred corrections (SDC) and its variants multi-level SDC and PFASST. pySDC is intended for rapid prototyping and educational purposes. New ideas like e.g. sweepers and preconditioners can be tested and first toy problems can be easily implemented. Time-parallel runs can be performed either in parallel using mpi4py or, in order to avoid technical or debugging issues, in serial using emulated parallelism.We will first give a brief introduction to the design, capabilities and limitations of the code. Then, if installation goes well, participants can create and run their own examples, and learn how to implement a new, time-parallel sweeper.For the hands-on session, participants need a Python installation (3.7 or above) with recent versions of the packages numpy, scipy, matplotlib, and mpi4py. We strongly recommend using a virtual environment with conda or mamba. Details can be found in the README file here: https://github.com/Parallel-in-Time/pySDC/blob/master/pySDC/playgrounds/12th_PinT_Workshop/README.rst 001018544 536__ $$0G:(DE-HGF)POF4-5112$$a5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0 001018544 536__ $$0G:(EU-Grant)955701$$aTIME-X - TIME parallelisation: for eXascale computing and beyond (955701)$$c955701$$fH2020-JTI-EuroHPC-2019-1$$x1 001018544 536__ $$0G:(DE-Juel-1)RG-RSE$$aRGRSE - RG Research Software Engineering for HPC (RG RSE) (RG-RSE)$$cRG-RSE$$x2 001018544 7001_ $$0P:(DE-Juel1)190575$$aBaumann, Thomas$$b1$$ufzj 001018544 8564_ $$uhttps://juser.fz-juelich.de/record/1018544/files/talk_PinT12_202307_rs.pdf$$yOpenAccess 001018544 8564_ $$uhttps://juser.fz-juelich.de/record/1018544/files/talk_PinT12_202307_rs.gif?subformat=icon$$xicon$$yOpenAccess 001018544 8564_ $$uhttps://juser.fz-juelich.de/record/1018544/files/talk_PinT12_202307_rs.jpg?subformat=icon-1440$$xicon-1440$$yOpenAccess 001018544 8564_ $$uhttps://juser.fz-juelich.de/record/1018544/files/talk_PinT12_202307_rs.jpg?subformat=icon-180$$xicon-180$$yOpenAccess 001018544 8564_ $$uhttps://juser.fz-juelich.de/record/1018544/files/talk_PinT12_202307_rs.jpg?subformat=icon-640$$xicon-640$$yOpenAccess 001018544 909CO $$ooai:juser.fz-juelich.de:1018544$$popenaire$$pdriver$$pVDB$$popen_access$$pec_fundedresources 001018544 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132268$$aForschungszentrum Jülich$$b0$$kFZJ 001018544 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)190575$$aForschungszentrum Jülich$$b1$$kFZJ 001018544 9131_ $$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 001018544 9141_ $$y2023 001018544 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess 001018544 920__ $$lyes 001018544 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0 001018544 980__ $$alecture 001018544 980__ $$aVDB 001018544 980__ $$aI:(DE-Juel1)JSC-20090406 001018544 980__ $$aUNRESTRICTED 001018544 9801_ $$aFullTexts