Parallel simulation for a fish schooling model on a general-purpose graphics processing unit

Authors:
Hong Li;Allison Kolpas;Linda Petzold;Jeff Moehlis
Affiliations:
Department of Computer Science, University of California, Santa Barbara, CA 93106, U.S.A.;Department of Mathematics, University of California, Santa Barbara, CA 93106, U.S.A.;Department of Computer Science, University of California, Santa Barbara, CA 93106, U.S.A. and Department of Mechanical Engineering, University of California, Santa Barbara, CA 93106, U.S.A.;Department of Mechanical Engineering, University of California, Santa Barbara, CA 93106, U.S.A.
Venue:
Concurrency and Computation: Practice & Experience
Year:
2009

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Abstract

We consider an individual-based model for fish schooling, which incorporates a tendency for each fish to align its position and orientation with an appropriate average of its neighbors' positions and orientations, in addition to a tendency for each fish to avoid collisions. To accurately determine the statistical properties of the collective motion of fish whose dynamics are described by such a model, many realizations are typically required. This carries a very high computational cost. The current generation of graphics processing units is well suited to this task. We describe our implementation and present computational experiments illustrating the power of this technology for this important and challenging class of problems. Copyright © 2008 John Wiley & Sons, Ltd.