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

Authored by Allison Kolpas, Hong Li, Linda Petzold, Jeff Moehlis

Date Published: 2009

DOI: 10.1002/cpe.1330

Sponsors: Alfred P. Sloan Foundation United States National Institutes of Health (NIH) United States Department of Energy (DOE) United States National Science Foundation (NSF)

Platforms: C

Model Documentation: Other Narrative

Model Code URLs: Model code not found

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 (C) 2008 John Wiley \& Sons, Ltd.

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