ExaHyPE: An engine for parallel dynamically adaptive simulations of wave problems
| dc.contributor.author | Reinarz, Anne | |
| dc.contributor.author | Charrier, Dominic E. | |
| dc.contributor.author | Bader, Michael | |
| dc.contributor.author | Bovard, Luke | |
| dc.contributor.author | Dumbser, Michael | |
| dc.contributor.author | Duru, Kenneth | |
| dc.contributor.author | Fambri, Francesco | |
| dc.contributor.author | Gabriel, Alice-Agnes | |
| dc.contributor.author | Gallard, Jean-Matthieu | |
| dc.contributor.author | Koppel, Sven | |
| dc.contributor.author | Krenz, Lukas | |
| dc.date.accessioned | 2023-02-28T00:49:28Z | |
| dc.date.available | 2023-02-28T00:49:28Z | |
| dc.date.issued | 2020 | |
| dc.date.updated | 2021-12-26T07:17:22Z | |
| dc.description.abstract | ExaHyPE (“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.sponsorship | This 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.mimetype | application/pdf | en_AU |
| dc.identifier.issn | 0010-4655 | en_AU |
| dc.identifier.uri | http://hdl.handle.net/1885/286501 | |
| dc.language.iso | en_AU | en_AU |
| dc.provenance | Published 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.publisher | Elsevier | en_AU |
| dc.rights | © 2020 The authors | en_AU |
| dc.rights.license | Creative Commons Attribution licence | en_AU |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_AU |
| dc.source | Computer Physics Communications | en_AU |
| dc.subject | Hyperbolic | en_AU |
| dc.subject | PDE | en_AU |
| dc.subject | ADER-DG | en_AU |
| dc.subject | Finite volumes | en_AU |
| dc.subject | AMR | en_AU |
| dc.subject | MPI | en_AU |
| dc.subject | TBB | en_AU |
| dc.subject | MPI+X | en_AU |
| dc.title | ExaHyPE: An engine for parallel dynamically adaptive simulations of wave problems | en_AU |
| dc.type | Journal article | en_AU |
| dcterms.accessRights | Open Access | en_AU |
| local.contributor.affiliation | Reinarz, Anne, Technical University of Munich | en_AU |
| local.contributor.affiliation | Charrier, Dominic E., Durham University | en_AU |
| local.contributor.affiliation | Bader, Michael, Technical University of Munich | en_AU |
| local.contributor.affiliation | Bovard, Luke, Goethe University | en_AU |
| local.contributor.affiliation | Dumbser, Michael, University of Trento | en_AU |
| local.contributor.affiliation | Duru, Kenneth, College of Science, ANU | en_AU |
| local.contributor.affiliation | Fambri, Francesco, Max-Planck-Institute for Plasma Physics | en_AU |
| local.contributor.affiliation | Gabriel, Alice-Agnes, Ludwig-Maximilian University | en_AU |
| local.contributor.affiliation | Gallard, Jean-Matthieu, Technical University of Munich | en_AU |
| local.contributor.affiliation | Koppel, Sven, Goethe University | en_AU |
| local.contributor.affiliation | Krenz, Lukas, Technical University of Munich | en_AU |
| local.contributor.authoruid | Duru, Kenneth, u1074121 | en_AU |
| local.description.notes | Imported from ARIES | en_AU |
| local.identifier.absfor | 490303 - Numerical solution of differential and integral equations | en_AU |
| local.identifier.absfor | 460607 - High performance computing | en_AU |
| local.identifier.absfor | 460104 - Applications in physical sciences | en_AU |
| local.identifier.absseo | 280110 - Expanding knowledge in engineering | en_AU |
| local.identifier.absseo | 220401 - Application software packages | en_AU |
| local.identifier.absseo | 280118 - Expanding knowledge in the mathematical sciences | en_AU |
| local.identifier.ariespublication | a383154xPUB11477 | en_AU |
| local.identifier.citationvolume | 254 | en_AU |
| local.identifier.doi | 10.1016/j.cpc.2020.107251 | en_AU |
| local.identifier.scopusID | 2-s2.0-85081228666 | |
| local.publisher.url | https://www.sciencedirect.com/ | en_AU |
| local.type.status | Published Version | en_AU |
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