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ExaHyPE: An Engine for Parallel Dynamically Adaptive Simulations of Wave Problems

Authors :
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
Publication Year :
2019

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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1905.07987
Document Type :
Working Paper
Full Text :
https://doi.org/10.1016/j.cpc.2020.107251