Stochastic differential equations (3rd ed.): an introduction with applications
Stochastic differential equations (3rd ed.): an introduction with applications
Physically-based visual simulation on graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Programmable Stream Processors
Computer
Hardware-based simulation and collision detection for large particle systems
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
MASON: A Multiagent Simulation Environment
Simulation
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Adaptive algorithms for the dynamic distribution and parallel execution of agent-based models
Journal of Parallel and Distributed Computing - Special issue on parallel bioinspired algorithms
Impostors and pseudo-instancing for GPU crowd rendering
Proceedings of the 4th international conference on Computer graphics and interactive techniques in Australasia and Southeast Asia
Data parallel execution challenges and runtime performance of agent simulations on GPUs
Proceedings of the 2008 Spring simulation multiconference
Proceedings of the 9th International Conference on Computational Methods in Systems Biology
Smoldyn on Graphics Processing Units: Massively Parallel Brownian Dynamics Simulations
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Simulation and study of large-scale bacteria-materials interactions via BioScape enabled by GPUs
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
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Agent-based modeling has been recognized as a method to bridge the translational gap in integrative systems biology. However, the computational complexity of agent-based models at biologically relevant scales makes simulation impractical on traditional CPU-based serial computing. In this paper we present a series of algorithms for simulating large scale agent-based models on graphics processing units (GPUs). GPUs have recently emerged as a powerful and economical computing platform for certain applications in scientific computing. As a test case, we have implemented an agent-based model of tuberculosis. This model simulates the interaction of the human immune system in the lung with Mycobacterium tuberculosis and tracks the formation of characteristic structures called granulomas. The model uses mobile agents to represent immune cells such as T cells and macrophages, field equations representing effector chemokines, and bacteria. Algorithms were implemented and benchmarked against a CPU implementation. Our benchmarks show performance gains of over 100 for moderately sized models. This opens the possibility of efficiently simulating realistically sized models on desktop computers.