How to run the code

Once installed (see Installation), FBPIC is available as a Python module on your system. Thus, a simulation is setup by creating a Python script that imports and uses FBPIC’s functionalities.

Script examples

You can download examples of FBPIC scripts below (which you can then modify to suit your needs):

(See the documentation of Particles.make_ionizable for more information on ionization, and the section Running boosted-frame simulations for more information on the boosted frame.)

The different FBPIC objects that are used in the above simulation scripts are defined in the section API reference.

Running the simulation

The simulation is then run by typing


where should be replaced by the name of your Python script: either or for the above examples.


When running on CPU, multi-threading is enabled by default, and the default number of threads is the number of cores on your system. You can modify this with environment variables:

  • To modify the number of threads (e.g. set it to 8 threads):
  • To disable multi-threading altogether (except for the FFT and DHT):


When running on GPU with MPI domain decomposition, it is possible to enable the CUDA GPUDirect technology. GPUDirect enables direct communication of CUDA device arrays between GPUs over MPI without explicitly copying the data to CPU first, resulting in reduced latencies and increased bandwidth. As this feature requires a CUDA-aware MPI implementation that supports GPUDirect, it is disabled by default and should be used with care.

To activate this feature, the user needs to set the following environment variable:


Visualizing the simulation results

The code outputs HDF5 files, that comply with the openPMD standard. As such, they can be visualized for instance with the openPMD-viewer). To do so, first install the openPMD-viewer by typing

conda install -c rlehe openpmd_viewer

And then type


and follow the instructions in the notebook that pops up. (NB: the notebook only shows some of the capabilities of the openPMD-viewer. To learn more, see the tutorial notebook on the Github repository of openPMD-viewer).