GPU acceleration of cell-based simulations in Chaste using FLAME GPU 2

Chaste is an open-source C++ library providing a general-purpose framework for cell-based simulations of biological tissues. It has been applied to a wider range of biological processes, including morphogenesis, carcinogenesis, and wound healing. Such simulations often involve numerous mechanical interactions between neighbouring cells, making them computationally demanding. Graphical Processing Units (GPUs), with their highly parallel architectures, offer a powerful means to accelerate these computations, enabling larger, more detailed simulations and improving research productivity. FLAME GPU 2 is a GPU-accelerated simulator for domain-independent complex systems that maps formal agent descriptions written in scripting language to optimized CUDA code. In this work, FLAME GPU 2 is integrated with Chaste to accelerate force calculations in a class of cell-based simulations, demonstrating the feasibility of GPU acceleration within existing CPU-based frameworks. The GPU-accelerated implementation is validated against the original CPU version, achieving up to 93.6x speedup in force calculations and 3.72x speedup for full simulations across various cell population sizes. Moreover, the approach enables smaller mechanics time steps, without incurring significant data transfer overhead, thereby improving the accuracy of mechanical modelling. This enhancement increases the fidelity of cell position calculations in non-equilibrium simulations and improves dynamic accuracy as cells approach equilibrium.

Authors

Institutions

Publication Details

Journal
Mathematics in Medical and Life Sciences
Published
2026-11-04
DOI
https://doi.org/10.1080/29937574.2026.2754441
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

GPU acceleration of cell-based simulations in Chaste using FLAME GPU 2

Paul Richmond, Alexander George Fletcher, Peter Heywood, Matthew J. Leach
1 links
Mathematics in Medical and Life Sciences
Parallel Computing and Optimization Techniques
article

GPU acceleration of cell-based simulations in Chaste using FLAME GPU 2

Paul Richmond, Alexander George Fletcher, Peter Heywood, Matthew J. Leach
article en

Abstract

Chaste is an open-source C++ library providing a general-purpose framework for cell-based simulations of biological tissues. It has been applied to a wider range of biological processes, including morphogenesis, carcinogenesis, and wound healing. Such simulations often involve numerous mechanical interactions between neighbouring cells, making them computationally demanding. Graphical Processing Units (GPUs), with their highly parallel architectures, offer a powerful means to accelerate these computations, enabling larger, more detailed simulations and improving research productivity. FLAME GPU 2 is a GPU-accelerated simulator for domain-independent complex systems that maps formal agent descriptions written in scripting language to optimized CUDA code. In this work, FLAME GPU 2 is integrated with Chaste to accelerate force calculations in a class of cell-based simulations, demonstrating the feasibility of GPU acceleration within existing CPU-based frameworks. The GPU-accelerated implementation is validated against the original CPU version, achieving up to 93.6x speedup in force calculations and 3.72x speedup for full simulations across various cell population sizes. Moreover, the approach enables smaller mechanics time steps, without incurring significant data transfer overhead, thereby improving the accuracy of mechanical modelling. This enhancement increases the fidelity of cell position calculations in non-equilibrium simulations and improves dynamic accuracy as cells approach equilibrium.

Mathematics in Medical and Life SciencesVol. 3(1)
University of Sheffield (GB)
Openalex Percentile: Top 98%
Parallel Computing and Optimization Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon