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ISSN: 1543-1649 Print
ISSN: 1940-4352 Online
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DOI: 10.1615/IntJMultCompEng.v9.i2
Pages: 118
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DOI: 10.1615/IntJMultCompEng.v9.i2.50
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Article price - $35.00 |
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SEECN: SIMULATING COMPLEX SYSTEMS USING DYNAMIC COMPLEX NETWORKS
Rick Quax
Computational Science, University of Amsterdam, Netherlands
David A. Bader
College of Computing, Georgia Institute of Technology, USA
Peter M. A. Sloot
Computational Science, University of Amsterdam, Netherlands
ABSTRACT
Multiscale, multiphysics systems are too complex for traditional mathematical modeling and require numerical simulation, yet such systems arise everywhere from modeling the immune system and protein interaction to epidemic spread in a human population. Unfortunately, at present researchers create their own ad hoc programs for their particular study. To address this problem we present the simulator for efficient evolution on complex networks (SEECN), an expressive simulator of complex systems that optimizes for both single-core and parallel performance. In SEECN, a complex network represents the system where the nodes and edges have specified properties that dictate the dynamics of the network over time. Our application is a detailed model of HIV spread among men who have sex with men and serves to show the simulator's expressiveness and to evaluate its performance.
Keywords: multiscale, multiphysics, modeling, simulation, complex systems, complex networks
pages 201-214
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