Parallel discrete-event simulation of FCFS stochastic queueing networks
PPEALS '88 Proceedings of the ACM/SIGPLAN conference on Parallel programming: experience with applications, languages and systems
PADS '93 Proceedings of the seventh workshop on Parallel and distributed simulation
Automated parallelization of timed Petri-net simulations
Journal of Parallel and Distributed Computing
On extending parallelism to serial simulators
PADS '95 Proceedings of the ninth workshop on Parallel and distributed simulation
PADS '95 Proceedings of the ninth workshop on Parallel and distributed simulation
Experiments in automated load balancing
PADS '96 Proceedings of the tenth workshop on Parallel and distributed simulation
Dynamic load balancing in parallel discrete event simulation for spatially explicit problems
PADS '98 Proceedings of the twelfth workshop on Parallel and distributed simulation
Experiments in load migration and dynamic load balancing in SPEEDES
Proceedings of the 30th conference on Winter simulation
PADS '99 Proceedings of the thirteenth workshop on Parallel and distributed simulation
Partitioning WCN models for parallel simulation of radio resource management
Wireless Networks - Special issue: Design and modeling in mobile and wireless systsems
Simulating spatially explicit problems on high performance architectures
Journal of Parallel and Distributed Computing - Parallel and Distributed Discrete Event Simulation--An Emerging Technology
Journal of Parallel and Distributed Computing
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Parallel discrete event simulation offers the potential for significant speedup over sequential simulation. Unfortunately, high performance is often achieved only after rigorous fine tuning is used to obtain an efficient mapping of tasks to processors. In practice, good performance with minimal effort is often preferable to high performance with excessive effort. We discuss our research in adding automated load balancing to the SPEEDES simulation framework. Using simulation models of queuing networks and the National Airspace System, we demonstrate that using run time measurements, our automated load balancing scheme can achieve better performance than simple allocation methods that do not use run time measurements, particularly when large numbers of processors are used.