Data-parallel techniques for simulating a mega-scale agent-based model of systemic inflammatory response syndrome on graphics processing units

Agent-based modeling is increasingly being used for computer simulation of complex biological systems. An agent-based model (ABM) is a bottom-up simulation where the bulk dynamics of the model result from the local interactions of its individual constituents or agents. However, due to emergent qualities of ABMs, bulk behaviors may be sensitive to the size of the model as determined by the population of individuals. Therefore, in certain circumstances it may be critical to closely match the simulation size with the actual system. This may be particularly true in biological systems, where multiple large-scale heterogeneous populations can range into millions or even billions of individual cells/agents. Most existing ABM simulation toolkits are designed for serial computing and canno*t effectively simulate such mega-scale systems from a run-time standpoint. In this paper, we investigate data-parallel ABM implementations on graphics processing units to address the scalability issue of ABMs. As an example, we have implemented an abstracted version of the Systemic Inflammatory Response Syndrome ABM. We also implemented a serial version to confirm statistical accuracy. Our results show that parallelization on graphics processing units offers a substantial gain in performance without a loss in accuracy.

[1]  Matthias Scheutz,et al.  and Parallel Execution of Agent-Based Models , 2005 .

[2]  C. Anthony Hunt,et al.  Physiologically based synthetic models of hepatic disposition - eScholarship , 2006 .

[3]  Nigel Gilbert,et al.  Platforms and methods for agent-based modeling , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Massimo Bernaschi,et al.  OpenMP parallelization of agent-based models , 2005, Parallel Comput..

[5]  Gerson G. H. Cavalheiro,et al.  An Efficient Parallel Algorithm to Evolve Simulations of the Cellular Potts Model , 2005, Parallel Process. Lett..

[6]  R. D'Souza.  SUGARSCAPE ON STEROIDS : SIMULATING OVER A MILLION AGENTS , 2007 .

[7]  Andreas Kolb,et al.  Hardware-based simulation and collision detection for large particle systems , 2004, Graphics Hardware.

[8]  R. Keyes.  Physical limits of silicon transistors and circuits , 2005 .

[9]  Brian Logan,et al.  Simulating agent-based systems with HLA: The case of SIM AGENT-Part II , 2003 .

[10]  S. Asano,et al.  The design and implementation of a first-generation CELL processor , 2005, ISSCC. 2005 IEEE International Digest of Technical Papers. Solid-State Circuits Conference, 2005..

[11]  Steven L. Lytinen,et al.  Agent-based Simulation Platforms: Review and Development Recommendations , 2006, Simul..

[12]  Matthias Scheutz,et al.  Adaptive algorithms for the dynamic distribution and parallel execution of agent-based models , 2006, J. Parallel Distributed Comput..

[13]  Jie Cheng,et al.  Programming Massively Parallel Processors. A Hands-on Approach , 2010, Scalable Comput. Pract. Exp..

[14]  R. Axelrod.  Agent-based Modeling as a Bridge Between Disciplines , 2006 .

[15]  Anselmo Lastra,et al.  Physically-based visual simulation on graphics hardware , 2002, HWWS '02.

[16]  Michael J. Quinn,et al.  PARALLEL IMPLEMENTATION OF THE SOCIAL FORCES MODEL , 2003 .

[17]  Wayne Luk,et al.  A comparison of CPUs, GPUs, FPGAs, and massively parallel processor arrays for random number generation , 2009, FPGA '09.

[18]  G An,et al.  Agent-based computer simulation and sirs: building a bridge between basic science and clinical trials. , 2001, Shock.

[19]  Erik Millán,et al.  Impostors and pseudo-instancing for GPU crowd rendering , 2006, GRAPHITE '06.

[20]  Michael S. Roberts,et al.  Physiologically Based Synthetic Models of Hepatic Disposition , 2006, Journal of Pharmacokinetics and Pharmacodynamics.

[21]  Kenichi Miura,et al.  Performance Improvement Methodology for ClearSpeed's CSX600 , 2007, 2007 International Conference on Parallel Processing (ICPP 2007).

[22]  Nan Chen,et al.  A Parallel Implementation of the Cellular Potts Model for Simulation of Cell-Based Morphogenesis , 2006, ACRI.

[23]  Morgan C. Giddings,et al.  An Agent-Based Model of Signal Transduction in Bacterial Chemotaxis , 2010, PloS one.