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ExaHyPE 2

www.exahype.org

ExaHyPE is an open source simulation engine to solve hyperbolic PDE systems. It is built on top of dynamically adaptive Cartesian meshes and offers support for Finite Volume, Runge-Kutta Discontinuous Galerkin and ADER-DG discretisations. 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.

The original ExaHyPE project (and therefore code) received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671698 (project ExaHyPE). After the project has successfully completed, we decided to completely rewrite, clean up and improve the code base. We decided to write ExaHyPE 2. ExaHyPE 2 is now completely integrated into its AMR baseline Peano 4 (which is a complete rewrite, too, where we also learned from the original ExaHyPE project), and it is shipped as part of this code/repository as a toolbox or extension. Download Peano and you get ExaHyPE 2. Peano’s guidebook documents how to use the engine, Peano’s license also holds for ExaHyPE 2, and Peano’s repository and Slack structure provide the infrastructure for ExaHyPE.

Funding

ExaHyPE today 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. Its core development in the UK is heavily supported by the UK’s exascale programme ExCALIBUR, and further support is provided via smaller national grants in both Germany and the UK.

Please consult the project pages to the right for some examples for ongoing projects around ExaHyPE.

Legacy code base

ExaHyPE 2 continues to be is hosted at the gitlab of the Leibniz Supercomputing Centre. The official project website continues to be exahype.eu, while we make the URL exahype.org point to the new developments, i.e. this page. You find “historic” information about the first generation of ExaHyPE at the eu address. The git repository remains available for download, though very few people still improve the code base due to the rewrite and integration into Peano 4.

Description

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

If you prefer a more computer science-focused explanation of the rationale and design decisions behind ExaHyPE and ExaHyPE 2, which they inherit directly from their AMR code base Peano, please read the ACM TOMS paper (ACM TOMS 45 (2), 2019).

@tobiasweinzierl.bsky.social

  • I've finally updated my project pages describing our long-standing and fruitful collaboration with Intel at @durham.ac.uk : https://tobiasweinzierl.webspace.durham.ac.uk/intel-academic-centre-of-excellence/
  • We will feature our HAI-End and @shareing.bsky.social projects in collaboration with @durham-comp-sci.bsky.social and @arc-durhamuni.bsky.social at the conference as well. Thanks to @cake-dri.bsky.social for making this possible. [contains quote post or other embedded content]
  • This is a great contribution highlighting the importance of this event. If you find it interesting, the @shareing.bsky.social team has also a blog on it: https://shareing-dri.github.io/blogpost/dri-retreat-26/ [contains quote post or other embedded content]
  • Had a brilliant time down in Abingdon to learn more about the National Federated Compute Services NetworkPlus initiative: nfcs-networkplus.ac.uk Looking forward to read about their roadmap later this year.
  • Our @shareing.bsky.social project has a new call open (shareing-dri.github.io/task-map/). We are searching for projects: You propose a project and whatever you want to do around accelerate computing, as long as you meet at least one of the tasks/outcomes that the SHAREing team has identified. https://shareing-dri.github.io/task-map/