We present a new technique for controlling optimism in Parallel Discrete Event Simulation on multicores. It is designed to be suitable for simulating models, in which the time intervals between successive events between different processes are highly variable, and have no lower bounds. In our technique, called Dynamic Local Time Window Estimates (DLTWE), each processor communicates time estimates of its next inter-processor event to (some of) its neighbors, which use the estimates as bounds for advancement of their local simulation time. We have implemented our technique in a parallel simulator for simulation of spatially extended Markovian processes of interacting entities, which can model chemical reactions, processes from biology, epidemics, and many other applications. Intervals between successive events are exponentially distributed, thus having a significant variance and no lower bound. We show that the DLTWE technique can be tuned to drastically reduce the frequency of rollbacks and enable speedups which is superior to that obtained by other works. We also show that the DLTWE technique significantly improves performance over other existing techniques for optimism control that attempt to predict arrival of inter-process events by statistical techniques.
The proposal in REF , still targeting multi-core architectures as we do, proposes a technique called Dynamic Local Time Window Estimates (DLTWE), in which each processor communicates time estimates of its next inter-processor event to its neighbors, which use the estimates as bounds for advancement.
Efficient Inter-Process Synchronization for Parallel Discrete Event Simulation on Multicores
SIGSIM PADS '15
Computer Science