ACM Transactions on Programming Languages and Systems (TOPLAS)
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
Parallel discrete event simulation
Communications of the ACM - Special issue on simulation
A generalized carrier-null method for conservative parallel simulation
PADS '94 Proceedings of the eighth workshop on Parallel and distributed simulation
Cooperative acceleration: robust conservative distributed discrete event simulation
PADS '94 Proceedings of the eighth workshop on Parallel and distributed simulation
A performance evaluation methodology for parallel simulation protocols
PADS '96 Proceedings of the tenth workshop on Parallel and distributed simulation
Parallel simulation environment for mobile wireless networks
WSC '96 Proceedings of the 28th conference on Winter simulation
Transparent implementation of conservative algorithms in parallel simulation languages
WSC '93 Proceedings of the 25th conference on Winter simulation
Synchronized data distribution management in distributed simulations
PADS '98 Proceedings of the twelfth workshop on Parallel and distributed simulation
GloMoSim: a library for parallel simulation of large-scale wireless networks
PADS '98 Proceedings of the twelfth workshop on Parallel and distributed simulation
Optimal performance of distributed simulation programs
WSC '87 Proceedings of the 19th conference on Winter simulation
Improving Lookahead in Parallel Wireless Network Simulation
MASCOTS '98 Proceedings of the 6th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Lookahead revisited in wireless network simulations
Proceedings of the sixteenth workshop on Parallel and distributed simulation
Large-Scale TCP Models Using Optimistic Parallel Simulation
Proceedings of the seventeenth workshop on Parallel and distributed simulation
Large-scale network simulation techniques: examples of TCP and OSPF models
ACM SIGCOMM Computer Communication Review
Parallel simulation: distributed simulation systems
Proceedings of the 35th conference on Winter simulation: driving innovation
Evolutionary performance-oriented development of parallel programs by composition of components
Proceedings of the 5th international workshop on Software and performance
Using Manufacturing Process Flow for Time Synchronization in HLA-Based Simulation
DS-RT '05 Proceedings of the 9th IEEE International Symposium on Distributed Simulation and Real-Time Applications
Improving Lookahead in Parallel Multiprocessor Simulation Using Dynamic Execution Path Prediction
Proceedings of the 20th Workshop on Principles of Advanced and Distributed Simulation
Good news for parallel wireless network simulations
Proceedings of the 12th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
Improving performance of parallel simulation kernel for wireless network simulations
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Proceedings of the 5th International ICST Conference on Simulation Tools and Techniques
Proceedings of the 2013 Summer Computer Simulation Conference
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Architectural advances are making PDES more difficult. Processor speed improves much more quickly than interprocessor communication and memory. Lagging memory performance has a much greater impact on optimistic techniques, especially for large scale models, but conservative techniques require more small protocol messages and are therefore impacted by slow IPC. The performance of conservative PDES is heavily dependent on the lookahead available in the simulation model. Finding larger lookahead not only allows for increased parallelism, it also reduces the number of protocol messages required. In this paper, a global view of a PDES model as a set of data flows is presented. Using this view, the lookahead of the model can be optimized, resulting in a significant decrease in protocol messages, with only a marginal increase in computation, using realistic, detailed models as examples.