High-Performance and Scalable Agent-Based Simulation with BioDynaMo

Breitwieser, Lukas; Hesam, A.S.; Rademakers, Fons; Luna, Juan Gómez; Mutlu, Onur

doi:10.1145/3572848.3577480

High-Performance and Scalable Agent-Based Simulation with BioDynaMo

Title

High-Performance and Scalable Agent-Based Simulation with BioDynaMo

Author

Breitwieser, Lukas (CERN; ETH Zürich)
Hesam, A.S. (TU Delft Computer Engineering)
Rademakers, Fons (CERN)
Luna, Juan Gómez (ETH Zürich)
Mutlu, Onur (ETH Zürich)

Date

2023

Abstract

Agent-based modeling plays an essential role in gaining insights into biology, sociology, economics, and other fields. However, many existing agent-based simulation platforms are not suitable for large-scale studies due to the low performance of the underlying simulation engines. To overcome this limitation, we present a novel high-performance simulation engine. We identify three key challenges for which we present the following solutions. First, to maximize parallelization, we present an optimized grid to search for neighbors and parallelize the merging of thread-local results. Second, we reduce the memory access latency with a NUMA-aware agent iterator, agent sorting with a space-filling curve, and a custom heap memory allocator. Third, we present a mechanism to omit the collision force calculation under certain conditions. Our evaluation shows an order of magnitude improvement over Biocellion, three orders of magnitude speedup over Cortex3D and NetLogo, and the ability to simulate 1.72 billion agents on a single server. Supplementary Materials, including instructions to reproduce the results, are available at: https://doi.org/10.5281/zenodo.6463816

Subject

agent-based modeling
high-performance simulation
HPC
memory allocation
memory layout optimization
NUMA
parallel computing
performance evaluation
performance optimization
scalability
space-filling curve