Software architectures for fault-tolerant replications and multithreaded decompositions: Experiments with practical parallel simulation

Felipe Knop, Purdue University

Abstract

This thesis is concerned with the experimental development of parallel simulation tools that not only exploit diverse multiprocessor environments, but also allow parallel simulations to be built with reasonable effort. We work on two fronts: model replication and model decomposition. We describe the design of EcliPSe, a parallel simulation system for replicative applications whose programming interface is designed to enable easy parallelization of such programs. We investigate solutions to serializing bottlenecks that arise when samples are collected from many processes. We also examine how the structure of replicative applications can be exploited to provide fault tolerance with low execution overhead. Experiments using up to 128 workstations resulted in excellent performance, showing the scalability of the system. In model decomposition (also called parallel discrete-event simulation), we depart from the standard approach usually taken in current parallel tools and use the active-transaction approach. By obviating the need for explicitly sending messages, we make modeling easier for analysts that are not used to parallel programming constructs. We describe the design of the ParaSol model-decomposed parallel simulation tool. Using this threads-based tool as a testbed, we investigate how existing methods for model decomposition can be adapted to the active-transaction approach. We show, using performance experiments, that this approach does not incur a substantial run-time penalty. Finally, to demonstrate that ParaSol enables a simplified approach to implementing models, we use it to develop the first parallel implementation of the widely used GPSS simulation language. Initial performance experiments showed promising results: despite the overheads associated with model-decomposed parallel simulations, we were able to achieve a 34% reduction in execution time when going from two to four processors in a GPSS program execution.

Degree

Ph.D.

Advisors

Rego, Purdue University.

Subject Area

Computer science

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