A Hybrid MPI+OpenMP Solution of the Distributed Cluster-based Fish Schooling Simulator

Abstract Exploring the multi-core architecture is an important issue to obtaining high performance in parallel and distributed discrete-event simulations. However, the simulation features must fit on parallel programming model in order to increase the performance. In this paper we show our experience developing a hybrid MPI+OpenMP version of our parallel and distributed discrete- event individual-oriented fish schooling simulator. In the hybrid approach developed, we fit our simulation features in the following manner: the communication between the Logical Processes happens via message passing whereas the computing of the individuals by OpenMP threads. In addition, we propose a new data structure for partitioning the fish clusters which avoid the critical section in OpenMP code. As a result, the hybrid version significantly improves the total execution time for huge quantity of individuals, because it decreases both the communication and management of processes overhead, whereas it increases the utilization of cores with sharing of resources.