Installation on a local computer¶

Installing FBPIC¶

The installation requires the Anaconda distribution of Python. If Anaconda is not your default Python distribution, download and install it from here.

Installation steps:

Install the dependencies of FBPIC:
```
conda install -c conda-forge numba scipy pyfftw mpi4py
```
Note

If you want to run FBPIC on an Intel CPU (not applicable if you want to run on a Macbook with Apple Silicon, or on a GPU), you can additionally install mkl for better performance.
```
conda install -c conda-forge mkl
```
Install fbpic:
```
pip install fbpic
```
Note

If you want to run FBPIC through the PICMI interface, you can instead use
```
pip install fbpic[picmi]
```
Note

Instead of using a release, you can also install FBPIC from the sources, by cloning the code from Github, and executing python3 -m pip install . from the main directory. A shortcut for this is: python3 -m pip install git+https://github.com/fbpic/fbpic.git.
Optional: In order to be able to run the code on a GPU, install the additional package cupy as well as dependencies needed to enable GPU support in numba.

For CUDA versions below 12, install cupy and cuda-version (which will automatically install cudatoolkit), for example
```
conda install -c conda-forge cupy cuda-version=11.8
```
For CUDA 12+ which no longer provides the cudatoolkit package, explicit installation of cuda-nvcc and cuda-nvrtc is required
```
conda install -c conda-forge cupy cuda-version=12.0 cuda-nvcc cuda-nvrtc
```
Warning

In the above commands, you should choose a CUDA version that is compatible with your GPU driver. You can see the version of your GPU driver by typing the command nvidia-smi. You can then find the compatible CUDA versions using this table.

Potential issues¶

On Mac OSX, the package mpi4py can sometimes cause issues. If you observe that the code crashes with an MPI-related error, try installing mpi4py using MacPorts and pip. To do so, first install MacPorts. Then execute the following commands:

conda uninstall mpi4py
sudo port install openmpi-gcc48
sudo port select --set mpi openmpi-gcc48-fortran
pip install mpi4py

If you are running on an Apple Silicon machine, mkl is not available via conda. You can use brew instead:

brew install onednn

Running simulations¶

See the section How to run the code, for instructions on how to run a simulation.