Please note that this is an Open Alpha release for developers and power users only.
Users should wait for our Open Beta release!
PIConGPU is a fully relativistic, many GPGPU, 3D3V particle-in-cell (PIC) code. The Particle-in-Cell algorithm is a central tool in plasma physics. It describes the dynamics of a plasma by computing the motion of electrons and ions in the plasma based on Maxwell's equations.
PIConGPU implements various numerical schemes to solve the PIC cycle. Its features include:
- a Yee-lattice like grid structure
- particle pushers that solve the equation of motion for charged particles, e.g. the Boris- and the Vay-Pusher
- Maxwell field solvers, e.g. Yee's and Lehe's scheme
- rigorously charge conserving current deposition schemes, proposed by Villasenor-Buneman and Esirkepov
- macro-particle form factors ranging from NGP (0th order), CIC (1st), TSC(2nd) to PSQ (3rd)
Besides the central PIC algorithm, we developed a wide range of tools and diagnostics, e.g.:
- online, far-field radiation diagnostics for coherent and incoherent radiation emitted by charged particles
- full hdf5 restart and dumping capabilities
- 2D and 3D live view and diagnostics tools
Todays GPUs reach a performance up to TFLOP/s at considerable lower invest and maintenance cost compared to CPU-based compute architectures of similar performance. The latest high-performance systems (TOP500) are enhanced by accelerator hardware that boost their peak performance up to the multi-PFLOP/s level. With its outstanding performance, PIConGPU is one of the finalists of the 2013s Gordon Bell Prize.
PIConGPU is developed and maintained by the Junior Group Computational Radiation Physics at the Institute for Radiation Physics at HZDR in close collaboration with the Center for Information Services and High Performance Computing (ZIH) of the Technical University Dresden (TUD). We are a member of the Dresden CUDA Center of Excellence that cooperates on a broad range of scientific CUDA applications, workshops and teaching efforts.
PIConGPU is a scientific project. If you present and/or publish scientific results that used PIConGPU, you should set a reference to show your support.
Our according up-to-date publication at the time of your publication should be inquired from:
The following slide should be part of oral presentations. It is intended to acknowledge the team maintaining PIConGPU and to support our community:
(coming soon) presentation_picongpu.pdf (svg version, key note version, png version: 1920x1080 and 1024x768)
PIConGPU is licensed under the GPLv3+. You can use our libraries with GPLv3+ or LGPLv3+ (they are dual licensed). Please refer to our LICENSE.md
See our notes in INSTALL.md.
Dear User, please beware that this is a developer and power user only release! We hereby emphasize that you should wait for our Beta release.
Visit picongpu.hzdr.de to learn more about PIC codes. See the user guide, our getting started video and contact us!
Upgrades: Every time we update the master branch, we publish a new release
of PIConGPU. Before you pull the changes in, please read our ChangeLog!
You may have to update some of your simulation .param files by hand
(detailed upgrade guide coming soon).
See CONTRIBUTING.md
- Dr. Michael Bussmann
- Dr.-Ing. Guido Juckeland
- Heiko Burau*
- Dr. Alexander Debus
- Carlchristian Eckert
- Marco Garten
- Axel Huebl*
- Maximilian Knespel
- Richard Pausch*
- Felix Schmitt*
- Conrad Schumann
- Rene Widera*
- Benjamin Worpitz
The PIConGPU Team expresses its thanks to:
- Florian Berninger
- Robert Dietrich
- Wen Fu, PhD
- Anton Helm
- Wolfgang Hoehnig
- Dr. Remi Lehe
- Benjamin Schneider
- Joseph Schuchart
- Klaus Steiniger
Kudos to everyone who helped!
