Trading Computation Time for Synchronization Time in Spatial Distributed Simulation

We consider a class of models describing generic agents (e.g. macromolecules, small organisms) which are able to travel in space, can sense the surrounding environment, and can react accordingly. In these models, we focus on individual-based simulation. We start with defining a simple centralized simulation algorithm, which we then improve so to develop a distributed algorithm producing the same output. An analytical model is given to estimate the expected speedup of our distributed algorithm depending on several parameters. A main aspect of our approach is that it trades computation time for synchronization time. That is, we allow each node to perform apparently redundant computation whenever this reduces the amount of needed synchronization in such a way that the overall performance improves.