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001018968 0247_ $$2datacite_doi$$a10.34734/FZJ-2023-05038
001018968 037__ $$aFZJ-2023-05038
001018968 1001_ $$0P:(DE-Juel1)190575$$aBaumann, Thomas$$b0$$eCorresponding author
001018968 1112_ $$a12th Parallel-in-Time Workshop$$cHamburg$$d2023-07-17 - 2023-07-21$$wGermany
001018968 245__ $$apySDC: Prototyping Spectral Deferred Corrections
001018968 260__ $$c2023
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001018968 502__ $$cHamburg University of Technology
001018968 520__ $$aSpectral deferred corrections (SDC) is a very malleable time-stepping scheme that is especially well-suited for stiff problems. A wide range of parallel-in-time (PinT) extensions exist, from small-scale parallelism across the method to the large-scale PinT algorithm PFASST. SDC iteratively solves fully-implicit Runge-Kutta (RK) schemes with low-order methods. pySDC is a Python library that allows interested users to test how well SDC works for their specific problem or algorithm with very little effort. It includes implementations of PinT algorithms in both simulated parallel versions as well as MPI-based parallel versions. In addition, implementations of many popular serial RK methods are part of pySDC to enable a quick and fair comparison in an internally consistent framework. The code is very actively developed by collaborators in Juelich, Hamburg and Wuppertal. pySDC is publicly hosted on GitHub and extensively tested with continuous integration to ensure reproducibility and maintainability of the code and the results obtained with it. Contribution guidelines and tutorials exist to invite and guide new users. The modular nature allows developers to work on specific features without awareness of all details in the code, which encourages also smaller projects, such as master's theses.
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001018968 536__ $$0G:(EU-Grant)955701$$aTIME-X - TIME parallelisation: for eXascale computing and beyond (955701)$$c955701$$fH2020-JTI-EuroHPC-2019-1$$x1
001018968 7001_ $$0P:(DE-Juel1)132268$$aSpeck, Robert$$b1
001018968 7001_ $$0P:(DE-HGF)0$$aLunet, Thibaut$$b2
001018968 7001_ $$0P:(DE-HGF)0$$aRuprecht, Daniel$$b3
001018968 7001_ $$0P:(DE-HGF)0$$aWimmer, Lisa$$b4
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