BioDynaMo

BioDynaMo: A modular platform for high-performance agent-based simulation

Breitwieser, Lukas (CERN; ETH Zürich)
Hesam, A.S. (TU Delft Computer Engineering; CERN)
De Montigny, Jean (CERN)
Vavourakis, Vasileios (University of Cyprus; University College London)
Iosif, Alexandros (University of Cyprus)
Jennings, Jack (Newcastle University)
Kaiser, Marcus (Newcastle University; Shanghai Jiao Tong University; University of Nottingham Medical School)
Manca, Marco (SCimPulse Foundation)
Di Meglio, Alberto (CERN)
Al-Ars, Z. (TU Delft Computer Engineering)
Rademakers, Fons (CERN)
Mutlu, Onur (ETH Zürich)
Bauer, Roman (University of Surrey)

2022

Motivation: Agent-based modeling is an indispensable tool for studying complex biological systems. However, existing simulation platforms do not always take full advantage of modern hardware and often have a field-specific software design. Results: We present a novel simulation platform called BioDynaMo that alleviates both of these problems. BioDynaMo features a modular and high-performance simulation engine. We demonstrate that BioDynaMo can be used to simulate use cases in: neuroscience, oncology and epidemiology. For each use case, we validate our findings with experimental data or an analytical solution. Our performance results show that BioDynaMo performs up to three orders of magnitude faster than the state-of-the-art baselines. This improvement makes it feasible to simulate each use case with one billion agents on a single server, showcasing the potential BioDynaMo has for computational biology research.

http://resolver.tudelft.nl/uuid:58dbf255-f719-45d2-a816-1cdb356285b4

https://doi.org/10.1093/bioinformatics/btab649

1367-4803

Bioinformatics, 38 (2), 453-460

Institutional Repository

journal article

© 2022 Lukas Breitwieser, A.S. Hesam, Jean De Montigny, Vasileios Vavourakis, Alexandros Iosif, Jack Jennings, Marcus Kaiser, Marco Manca, Alberto Di Meglio, Z. Al-Ars, Fons Rademakers, Onur Mutlu, Roman Bauer