Techniques to improve the performance of large-scale discrete-event simulation

Abstract

Discrete-event simulation is a commonly used technique to model changes within a complex physical systems as a series of events that occur at discrete points of time. As the complexity of the physical system being modeled increases, the simulator can reach a point where it is no longer feasible for it to run efficiently on one computing resource. A common solution is to break the physical system into multiple logical processes. When breaking a simulation over multiple computing nodes, care must be taken to ensure the results obtained are the same as would be obtained from a non-distributed simulation. This is done by ensuring that the events processed in each individual logical process are processed in chronological order. The task is complicated by the fact that the computing nodes will be exchanging timestamped messages and will often be operating at different points of simulation time. Therefore, highly efficient synchronization methods must be used. It is also important that the logical processes have a capable means to transport messages among themselves or the benefits of parallelization will be lost. The objective of this dissertation is to design, develop, test, and evaluate tech- niques to improve the performance of large-scale discrete-event simulations. The techniques include improvements in messaging passing, state management, and time synchronization. Along with specific implementation improvements, we also examine techniques on how to effectively make use of resources such as shared memory and graphical processing units.