EU

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671698.

ExaHyPE is over - long live ExaHyPE!

The ExaHyPE project has been funded by the European Commission from 2015 until 2019. While the ExaHyPE Horizon 2020 project is over, the ExaHyPE software development continues -  see our section on the "ExaHyPE engine". We keep this website as an archive of the project achievements.

ExaHyPE Engine

The ExaHyPE engine has been released and is hosted on www.exahype.org


ExaHyPE is an open source simulation engine to solve hyperbolic PDE systems using
high-order ADER-DG discretisation. It is built on top of dynamically adaptive meshes
and a customisation engine to yield efficient parallel code.
ExaHyPE is written in a way that most computer science aspects as well as most of the
numerics are hidden away from the user. Users plug in user functions for their PDE formulation (such as flux functions and eigenvalues) into the engine and then delegate all further work to ExaHyPE.

Snapshots of the engine source code can be downloaded from www.exahype.org.
Access to the engine repository is granted after registration on the website.
The engine comes with a User Guide and several reference examples.

For details on the engine, see our article Reinarz et al. "ExaHyPE: An engine for parallel dynamically adaptive simulations of wave problems" (Comp. Phys. Comm. 254, 2020).

ExaHyPE received funding from the European Union's Horizon 2020 research and innovation
programme under grant agreement No 671698 (project ExaHyPE).

ExaHyPE is one of ten pilot codes targeted by the ChEESE Centre of Excellence in Solid Earth funded via the European Union's Horizon 2020 research and innovation programme
under grant agreement No 823844.

A slack channel for ExaHyPE exists, please contact This email address is being protected from spambots. You need JavaScript enabled to view it. for access.

EU

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671698.