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ExaHyPE: An engine for parallel dynamically adaptive simulations of wave problems

dc.contributor.authorReinarz, Anne
dc.contributor.authorCharrier, Dominic E.
dc.contributor.authorBader, Michael
dc.contributor.authorBovard, Luke
dc.contributor.authorDumbser, Michael
dc.contributor.authorDuru, Kenneth
dc.contributor.authorFambri, Francesco
dc.contributor.authorGabriel, Alice-Agnes
dc.contributor.authorGallard, Jean-Matthieu
dc.contributor.authorKoppel, Sven
dc.contributor.authorKrenz, Lukas
dc.date.accessioned2023-02-28T00:49:28Z
dc.date.available2023-02-28T00:49:28Z
dc.date.issued2020
dc.date.updated2021-12-26T07:17:22Z
dc.description.abstractExaHyPE (“An Exascale Hyperbolic PDE Engine”) is a software engine for solving systems of first-order hyperbolic partial differential equations (PDEs). Hyperbolic PDEs are typically derived from the conservation laws of physics and are useful in a wide range of application areas. Applications powered by ExaHyPE can be run on a student’s laptop, but are also able to exploit thousands of processor cores on state-of-the-art supercomputers. The engine is able to dynamically increase the accuracy of the simulation using adaptive mesh refinement where required. Due to the robustness and shock capturing abilities of ExaHyPE’s numerical methods, users of the engine can simulate linear and non-linear hyperbolic PDEs with very high accuracy. Users can tailor the engine to their particular PDE by specifying evolved quantities, fluxes, and source terms. A complete simulation code for a new hyperbolic PDE can often be realised within a few hours — a task that, traditionally, can take weeks, months, often years for researchers starting from scratch. In this paper, we showcase ExaHyPE’s workflow and capabilities through real-world scenarios from our two main application areas: seismology and astrophysics.en_AU
dc.description.sponsorshipThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671698, www.exahype.eu. The ExaHyPE team acknowledges additional support by the European Union’s Horizon 2020 research and innovation program (ChEESE, grant no. 823844). The authors gratefully acknowledge the support by the Leibniz Supercomputing Centre, Germany (www.lrz.de), which also provided the computing resources on SuperMUC (Grant No. pr48ma and Grant No. pr63qo) . We would especially like to thank the many people who have made contributions to ExaHyPE, in particular our previous team members Benjamin Hazelwood, Angelika Schwarz, Vasco Varduhn and Olindo Zanotti.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn0010-4655en_AU
dc.identifier.urihttp://hdl.handle.net/1885/286501
dc.language.isoen_AUen_AU
dc.provenancePublished by Elsevier B.V. This is an open access article under the CCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_AU
dc.publisherElsevieren_AU
dc.rights© 2020 The authorsen_AU
dc.rights.licenseCreative Commons Attribution licenceen_AU
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_AU
dc.sourceComputer Physics Communicationsen_AU
dc.subjectHyperbolicen_AU
dc.subjectPDEen_AU
dc.subjectADER-DGen_AU
dc.subjectFinite volumesen_AU
dc.subjectAMRen_AU
dc.subjectMPIen_AU
dc.subjectTBBen_AU
dc.subjectMPI+Xen_AU
dc.titleExaHyPE: An engine for parallel dynamically adaptive simulations of wave problemsen_AU
dc.typeJournal articleen_AU
dcterms.accessRightsOpen Accessen_AU
local.contributor.affiliationReinarz, Anne, Technical University of Munichen_AU
local.contributor.affiliationCharrier, Dominic E., Durham Universityen_AU
local.contributor.affiliationBader, Michael, Technical University of Munichen_AU
local.contributor.affiliationBovard, Luke, Goethe Universityen_AU
local.contributor.affiliationDumbser, Michael, University of Trentoen_AU
local.contributor.affiliationDuru, Kenneth, College of Science, ANUen_AU
local.contributor.affiliationFambri, Francesco, Max-Planck-Institute for Plasma Physicsen_AU
local.contributor.affiliationGabriel, Alice-Agnes, Ludwig-Maximilian Universityen_AU
local.contributor.affiliationGallard, Jean-Matthieu, Technical University of Munichen_AU
local.contributor.affiliationKoppel, Sven, Goethe Universityen_AU
local.contributor.affiliationKrenz, Lukas, Technical University of Munichen_AU
local.contributor.authoruidDuru, Kenneth, u1074121en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor490303 - Numerical solution of differential and integral equationsen_AU
local.identifier.absfor460607 - High performance computingen_AU
local.identifier.absfor460104 - Applications in physical sciencesen_AU
local.identifier.absseo280110 - Expanding knowledge in engineeringen_AU
local.identifier.absseo220401 - Application software packagesen_AU
local.identifier.absseo280118 - Expanding knowledge in the mathematical sciencesen_AU
local.identifier.ariespublicationa383154xPUB11477en_AU
local.identifier.citationvolume254en_AU
local.identifier.doi10.1016/j.cpc.2020.107251en_AU
local.identifier.scopusID2-s2.0-85081228666
local.publisher.urlhttps://www.sciencedirect.com/en_AU
local.type.statusPublished Versionen_AU

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