BioDynaMo: a modular platform for high-performance agent-based simulation.

Marco Manca,Alberto Di Meglio,Roman Bauer,Fons Rademakers,Marcus Kaiser,Alexandros Iosif,Zaid Al-Ars,Vasileios Vavourakis,Jack Jennings,Ahmad Hesam,Onur Mutlu,Jean de Montigny,Lukas Breitwieser

doi:10.1093/bioinformatics/btab649

Abstract

MotivationAgent-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.ResultsWe 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.Availability and implementationBioDynaMo is an open-source project under the Apache 2.0 license and is available at www.biodynamo.org. Instructions to reproduce the results are available in the supplementary information.Supplementary informationAvailable at https://doi.org/10.5281/zenodo.5121618.

Highlights

Agent-based simulation (ABS) is a powerful tool assisting life scientists in better understanding complex biological systems
We demonstrate that BioDynaMo can be used to simulate use cases in: neuroscience, oncology and epidemiology
We provide the following evidence to support this claim: (i) we detail the user-facing features of BioDynaMo that enable users to build a simulation based on predefined building blocks and to define a model tailored to their needs. (ii) We present three basic use cases in the field of neuroscience, oncology and epidemiology to demonstrate BioDynaMo’s capabilities and modularity. (iii) We show that BioDynaMo can produce biologically meaningful simulation results by validating these use cases against experimental data, or an analytical solution. (iv) We present performance data on different systems and scale each use case to one billion agents to demonstrate BioDynaMo’s performance

Summary

Introduction

Agent-based simulation (ABS) is a powerful tool assisting life scientists in better understanding complex biological systems. The effectiveness of such computer simulations for scientific research is often limited, in part because of two reasons. Most ABS platforms do not take full advantage of these hardware enhancements. The resulting limited computational power forces life scientists to compromise either on the resolution of the model or on simulation size (Thorne et al, 2007). Existing ABS platforms have often been developed with a specific use case in mind. This makes it challenging to implement the desired model, even if it deviates only slightly from its original purpose

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