pigreads 1.0.0

Python-integrated GPU-enabled reaction-diffusion solver

Pigreads

Pigreads is a streamlined, open-source Python module for efficient numerical solution of reaction–diffusion systems on graphics cards (GPUs), with CPU fallback. It exposes a minimal, concise, and NumPy-compatible API that allows users to define and run simulations while offloading the costly computations to accelerators via OpenCL kernels executed through PyOpenCL. The module supports 0D–3D uniform Cartesian grids, no-flux and periodic boundary conditions, anisotropic and spatially varying diffusion and reaction, and localised source terms. Pigreads includes several built-in models, including electrophysiology examples, while also allowing users to supply custom reaction terms, and is fully tested, documented, and distributed with examples and tutorials.

Peer-reviewed article

We have published a peer-reviewed article in Computer Physics Communications introducing Pigreads. It can be found at DOI 10.1016/j.cpc.2026.110088 or here. You may cite our article when using Pigreads:

Kabus, D., Dierckx, H., & De Coster, T. (2026). Pigreads: The Python-integrated GPU-enabled reaction-diffusion solver using OpenCL for cardiac electrophysiology and other applications. Computer Physics Communications, 110088.

@article{kabus2026pigreads,
  doi={10.1016/j.cpc.2026.110088},
  author={Desmond {Kabus} and Hans {Dierckx} and Tim {De Coster}},
  title={{Pigreads}: The {Python}-integrated {GPU}-enabled reaction-diffusion solver
    using {OpenCL} for cardiac electrophysiology and other applications},
  journal={Computer Physics Communications},
  pages={110088},
  year={2026},
  issn={0010-4655}
}

Getting started

Requirements

Pigreads uses OpenCL for calculations on the graphics cards. OpenCL is usually included in the drivers for your graphics card.

The following pages may help installing and accessing OpenCL:

• ArchWiki: OpenCL on Arch Linux
• OpenCL-Guide: OpenCL on Ubuntu Linux
• OpenCL-Guide: OpenCL on Windows
• Documentation of PyOpenCL.

You can use clinfo to verify you have an OpenCL platform installed.

If instead of the GPU, you want to use CPUs, you can install PoCL as an OpenCL platform to compute on the main processors.

Installation

Install this Python package in the standard way using pip, for instance from PyPI or from a local copy of this repository, see the Python documentation for details. To also install all optional dependencies, such as for the command line interface (CLI), run:

$ pip install pigreads[all] # from PyPI
$ pip install .[all] # from source

Note: If installing from source, you need to run python prepare.py first to render the code templates for the models that are defined as YAML in the models folder, and other preparation.

Usage

Simulations can be performed via calls to the Python module (API) or using the CLI. See the documentation for annotated examples, or the examples directory in the Pigreads repository.