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Peano 4

Peano is a framework for solvers operating on dynamically adaptive Cartesian meshes. It is the base for a couple of further engines or toolboxes for different application areas, while the framework is really only about the mesh management, data storage, distribution and mesh traversal. The latest version of Peano is the 4th generation of the code. It is completely free.

Codes built with Peano

Download

Peano and its extensions are hosted on the gitlab of the LRZ. We do not provide any regular snapshots, but you can always clone the latest version directly from the git:

git clone -b p4 https://gitlab.lrz.de/hpcsoftware/Peano.git

We are happy to give interested users write permissions to the repository such that they can merge their contributions into the public code base.

License

Peano has a BSD-like license. Clone the code and study the file COPY in the root folder. BSD-like means that you can basically do anything with the code including any commercial use, even if you directly inline code (what you have do if you use Peano’s templates). In return for all the freedom, we’d appreciate if you cited the code when you use it.

Documentation

Peano realises a relatively strict document-in-the-code paradigm. All the documentation (including tutorials, installation instructions, FAQs, description of the numerics, …) can be generated from the code through doxygen. The resulting documentation is generated after each push and can be found at

https://hpcsoftware.pages.gitlab.lrz.de/Peano/

If you want to generate the documentation locally, clone the repository and type in

doxygen documentation/Doxyfile

to create the documentation website on your machine.

Citing Peano

While Peano is a plain C++ code, most colleagues use it through its Python API. The API generates a lot of glue code plus a makefile such that Peano can run as stand-alone without any Python dependencies. It also generates a Readme file which clarifies which subcomponents of Peano you have used, where you find information about the underlying algorithmic concepts, and what to cite in this context. The Readme should be your first choice when you search for literature about the software.

If you search for a generic overview paper which describes the fundamental design principles and ideas and provides a first overview, please read the ACM TOMS paper

@article{Weinzierl:2019:Peano,
  author = 	 {T. Weinzierl},
  title = 	 {The Peano software---parallel, automaton-based, dynamically adaptive grid traversals},
  journal = 	 {ACM Transactions on Mathematical Software},
  year = 	 {2019},
  volume = 	 {45},
  number = 	 {2},
  pages = 	 {14}
}
  

@tobiasweinzierl.bsky.social

  • We had a very constructive kick off session for our 2025 performance analysis workshop series. Hope to be able to publish and share our insights and lessons learned soon.
  • It has been a privilege, fun, and extremely productive scientifically to be part of ExCALIBUR due to multiple projects. There are still many papers to come that directly result from this programme. [contains quote post or other embedded content]
  • It was great to have Prakash Murali from @cst.cam.ac.uk in our SciComp seminar today. Interesting ideas on full stack design in quantum computing.
  • Registration for the Durham HPC Days is open: https://pay.durham.ac.uk/event-durham/durham-hpc-days-2025. The programme is also getting there: https://durham.readthedocs.io/en/latest/hpcdays/index.html We now have 4.5 days packed with talks, tutorials and workshops!
  • I realise we've never published our SIAM BGCE contribution on arXiv. Here it is: arxiv.org/abs/2504.15814 We study stationary black holes phrased as wave equations over an adaptive mesh. The solution should be stationary by definition, but it is subject to numerical instabilities. https://arxiv.org/abs/2504.15814