ACM Transactions on Programming Languages and Systems (TOPLAS)
Parallel discrete event simulation
Communications of the ACM - Special issue on simulation
A multi-lingual optimistic distributed simulator
Transactions of the Society for Computer Simulation International
Synchronization mechanisms for distributed event-driven computation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
U.S. Army ModSim on Jade's timewarp
WSC '92 Proceedings of the 24th conference on Winter simulation
Using a shot clock to design an efficient parallel distributed simulation
WSC '94 Proceedings of the 26th conference on Winter simulation
Wolf: a rollback algorithm for optimistic distributed simulation systems
WSC '88 Proceedings of the 20th conference on Winter simulation
The time and state relationships in simulation modeling
Communications of the ACM - Special issue on simulation modeling and statistical computing
Distributed Simulation of Large-Scale PCS Networks
MASCOTS '94 Proceedings of the Second International Workshop on Modeling, Analysis, and Simulation On Computer and Telecommunication Systems
An adaptive partitioning algorithm for distributed discrete event simulation systems
Journal of Parallel and Distributed Computing - Problems in parallel and distributed computing: Solutions based on evolutionary paradigms
Journal of Parallel and Distributed Computing
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We compare the design and implementation of a parallel simulation of a traffic flow network using two different approaches: event-driven and time-driven. Our experiments with the sequential implementation of the two approaches correlates with previous research (Nance, 1971). We design a conservative parallel implementation of the traffic flow problem where we obtain a maximum speedup of 9.27 using 16 Sun workstations running under parallel virtual machine or PVM (Geist et al., 1993). We use wall-clock time as a measure of execution speed. We show that appreciable speedup can be achieved in parallelizing either the event-driven or time-driven approach. We also show that speedup is a misleading metric when used to compare the parallelizability of the two approaches. Parallel performance, as measured by speedup, may be better when the sequential performance is poor. For example, the time-driven implementation achieved better speedup than the event-driven implementation for few cars in the system; however the sequential time-driven implementation required longer to execute than the event-driven implementation for few cars in the system. Similarly for many cars in the system, the event-driven implementation achieved better speedup than the time-driven implementation.