Parallel simulation of group behaviors

Abstract

Group behaviors, e.g. birds flocking, are widely used in virtual reality, computer games, robotics and artificial life. While many methods to simulate group behaviors have been proposed, these methods are usually applied to sequential computing. Since the computational load of these methods is exponential to the number of group members, it is difficult to simulate a large group in real-time using these methods. In this paper, we propose a parallel algorithm to simulate the flocking behavior of a large group. The new partitioning and communication mechanisms in the parallel algorithm make the flocking simulation more efficient. Experimental results show that the proposed parallel algorithm provides good speedup in generating flocking behaviors compared with the sequential simulation.

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