Simulating Spatially Explicit Problems on High Performance Architectures

Abstract

This paper addresses issues of implementation and performance optimization of simulations designed to model spatially explicit problems with the use of parallel discrete event simulation. A simulation system is presented that uses the optimistic protocol and runs on a distributed memory machine—the IBM SP. The efficiency of parallel discrete event simulations that use the optimistic protocol is strongly dependent on the overhead incurred by rollbacks. This paper introduces a novel approach to rollback processing which limits the number of events rolled back as a result of a straggler or antimessage. The method, called Breadth-First Rollback (BFR), is suitable for spatially explicit problems where the space is discretized and distributed among processes and simulation objects move freely in the space. The BFR uses incremental state saving, allowing the recovery of causal relationships between events during rollback. These relationships are then used to determine which events need to be rolled back. This paper presents an application of BFR to the simulation of Lyme disease. Our results demonstrate and almost linear speedup—a dramatic improvement over the traditional approach to rollback processing. Additionally, BFR is used as a basis of a dynamic load balancing algorithm that migrates load between the simulation processes. A brief outline of the algorithm and its potential performance are presented.