Improving Communication Patterns for Distributed Cluster-based Individual-oriented Fish School Simulations

Abstract

Parallel discrete event simulation (PDES) have shown to be an useful paradigm for simulating complex and large-scale models. An individual-oriented approach allows modelers capture complex emerging global behaviors generated by simple local interaction, like observed in self-organized systems. Usually, this type of simulations are highly expensive in terms of computing and communications. One one hand, we can reduce the computing involved in individual interactions by means of developing a robust partitioning method. On the other hand, we have to be able to efficiently handle a huge number of individuals interacting with other individuals stored in memory of remote processors. In this work we will analyze and compare three communication strategies: synchronous and asynchronous message passing (via MPI) and bulk-synchronous parallel (BSP) for our distributed cluster-based individual-oriented fish school simulator. In this type of simulations, the main contributions of our work are: a) we showed that distributed time-driven simulations do not always improve the performance when using synchronous communication strategies, b) we show asynchronous communications strategies are more efficient. In addition, we have verified that the bulk-synchronous parallel method is a scalable.