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

Reinarz, Anne; Charrier, Dominic E.; Bader, Michael; Bovard, Luke; Dumbser, Michael; Duru, Kenneth; Fambri, Francesco; Gabriel, Alice-Agnes; Gallard, Jean-Matthieu; Köppel, Sven; Krenz, Lukas; Rannabauer, Leonhard; Rezzolla, Luciano; Samfass, Philipp; Tavelli, Maurizio; Weinzierl, Tobias

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Authors

Dominic E. Charrier

Michael Bader

Luke Bovard

Michael Dumbser

Kenneth Duru

Francesco Fambri

Alice-Agnes Gabriel

Jean-Matthieu Gallard

Sven Köppel

Lukas Krenz

Leonhard Rannabauer

Luciano Rezzolla

Philipp Samfass

Maurizio Tavelli



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.

Citation

Reinarz, A., Charrier, D. E., Bader, M., Bovard, L., Dumbser, M., Duru, K., …Weinzierl, T. (2020). ExaHyPE: An engine for parallel dynamically adaptive simulations of wave problems. Computer Physics Communications, 254, Article 107251. https://doi.org/10.1016/j.cpc.2020.107251

Journal Article Type Article
Acceptance Date Feb 25, 2020
Online Publication Date Mar 3, 2020
Publication Date Sep 30, 2020
Deposit Date Mar 3, 2020
Publicly Available Date Mar 28, 2024
Journal Computer Physics Communications
Print ISSN 0010-4655
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 254
Article Number 107251
DOI https://doi.org/10.1016/j.cpc.2020.107251

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