On computation and synchronization costs in spatial distributed simulation

We consider the problem of simulating spatially distributed entities which can move, see each other, and react accordingly. We provide centralized reference algorithms for both time-stepped and discrete-event simulation. Under reasonable assumptions, we then proceed to distribute the simulation among several nodes by assigning each node a subregion of the simulation space. A main characteristic of our approach is that the subregions do not form a partitioning, but a covering. That is, they partially overlap, hence causing some duplicated computation, which is apparently redundant. The amount of overlapping is a tunable parameter of our algorithms, which affects the overall performance in a non-trivial way. Through an analytical model as well as experimental results we discover a trade-off. Choosing a small overlapping requires to perform frequent synchronizations, which negatively affect performance. However, a large overlapping leads to more duplicated work, which also decreases performance. Balancing the amount of overlapping is then required to optimize performance.