An Empirical Study Of Combining Communicating Processes In A Parallel Discrete Event Simulation

An Empirical Study of Combining Communicating Processes in a Parallel Discrete Event Simulation

An Empirical Study of Combining Communicating Processes in a Parallel Discrete Event Simulation

The primary goal of distributed discrete event simulations is to achieve speedup in simulation execution time by distributing the processing of the simulation over multiple processors. When partitioned for distribution in this fashion, simulations are typically partitioned such that there are more processes than processors. This thesis reviews existing methods for distributed discrete event simulations, and proposes general guidelines for efficient partitioning for a given communications topology based on empirical evidence. A performance analysis is conducted for two approaches to partitioning the system. The first method chosen is a mapping of multiple processes to a processor and the second approach utilizes a distributed event list approach, developed by Mannix. This approach combines smaller processes into a larger single process, incorporating a next event list similar to that used in a sequential simulation. Empirical studies compare the performance of the two approaches under a variety of conditions. The traditional Chandy-Mirsa approach to system partitioning is demonstrated to yield overall better performance than the distributed event list algorithm. General guidelines for partitioning the system for both approaches are developed based on the performance comparisons.

Scientific and Technical Aerospace Reports