Pigreads: The Python-integrated GPU-enabled reaction-diffusion solver using OpenCL for cardiac electrophysiology and other applications

• GPU-accelerated reaction-diffusion solver in up to three dimensions. • Minimal NumPy-friendly API with OpenCL kernels. • Includes commonly used reaction terms for cardiac electrophysiology. • Open-source, tested, documented, with examples and tutorials. Pigreads is a streamlined Python module for efficient numerical solution of reaction-diffusion systems on graphics cards (GPU), with CPU fallback. It exposes a simple and straight-forward NumPy-compatible API. Users may employ built-in models – including electrophysiology examples – or supply custom reaction terms. Supported features include 0D-3D uniform Cartesian grids, no-flux and periodic boundary conditions, anisotropic diffusion, spatially varying diffusion and reaction, and localised source terms. The project is open-source, tested, documented, and distributed with examples and tutorials. PROGRAM SUMMARY Program Title: Pigreads CPC Library link to program files: https://doi.org/10.17632/5k8jjx74hc.1 Developer’s repository link: https://gitlab.com/pigreads/pigreads Licensing provisions: MIT Programming language: Python, OpenCL Nature of problem: Reaction-diffusion systems model phenomena across physics, chemistry and biology; their numerical solution can be computationally demanding and research codes are often ad-hoc and poorly documented. Solution method: The implementation uses finite-differences spatial discretisation and explicit forward-Euler time stepping. Performance-critical kernels run in OpenCL and are called from Python using PyOpenCL; data are represented with NumPy arrays. Additional comments including restrictions and unusual features: Pigreads targets reaction-diffusion problems with a focus on cardiac electrophysiology applications and emphasises simplicity and reproducibility over advanced numerical complexity. We adhere to best practices in scientific software development, including version control, testing, and continuous integration.