High performance individual-oriented simulation using complex models

Abstract Computational simulation has been used as a powerful tool to represent the dynamical behavior of systems based on complex analytic models. These types of models have two main drawbacks: (a) limitations due to the degree of abstraction needed to simulate them, (b) high computing power to simulate a heavily simplified models. The computing power available today can overcome these limitations to perform quicker simulations of complex models that are closer to reality. In this paper, the experiments and performance analysis of a distributed simulation for a complex individual oriented model (fish schools) are presented. The development of the fish school simulator includes the possibility of working with large models that include large numbers of fish (>106 of individuals), predators and obstacles in the simulated world.

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