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Acceleration of Multi-agent Simulation on FPGAs Open Access


Other title
Multi-agent Simulation
Type of item
Degree grantor
University of Alberta
Author or creator
Cui, Lintao
Supervisor and department
Hu, Yu (Electrical and Computer Engineering)
Examining committee member and department
Qiu, Zhijun (Civil and Environmental Engineering)
Han, Jie (Electrical and Computer Engineering)
Department of Electrical and Computer Engineering
Computer, Microelectronic Devices, Circuits and Systems
Date accepted
Graduation date
Master of Science
Degree level
Multi-Agent Simulation (MAS) is a widely used paradigm for modeling and simulating real world complex system, ranging from ant colony foraging to online trading. MAS describes a complex system by representing it as a collection of interactive and concurrent objects following a set of predefined rules. To run MAS, several software frameworks have been developed to enable easy MAS experimentation and implementation. The performance of those MAS software, however, suffers when simulating massive-scale multi-agent systems on traditional serial processing processors. To overcome the limitation of serial computing, a parallel platform is required. In this thesis, we propose a FPGA-based parallel framework to support massivescale MAS modeling and simulation. Memory interleaving, parallel tasks partition, and computing pipeline, i.e. a three-step methodology, are adopted to improve the system throughput and performance for massive-scale MAS applications. A classical MAS benchmark, Conway‘s Game of Life, is used as a case study to illustrate how to map a grid-based model to our MAS framework using the proposed methodology. We implemented it on a Xilinx Virtex-5 FPGA board and achieved a speedup of 290x with two million agents, compared to the C implementation.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
Lintao Cui; Jing Chen; Yu Hu; Jinjun Xiong; Zhe Feng; Lei He; , "Acceleration of Multi-agent Simulation on FPGAs," Field Programmable Logic and Applications (FPL), 2011 International Conference on , vol., no., pp.470-473, 5-7 Sept. 2011

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