ACM Transactions on Programming Languages and Systems (TOPLAS)
Performance evaluation of the time warp distributed simulation mechanism
Performance evaluation of the time warp distributed simulation mechanism
Discrete event simulations and parallel processing: statistical properties
SIAM Journal on Scientific and Statistical Computing
Parallel simulation of queueing networks: limitations and potentials
SIGMETRICS '89 Proceedings of the 1989 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Parallel discrete event simulation
Communications of the ACM - Special issue on simulation
A time-division algorithm for parallel simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
ACM SIGSIM Simulation Digest
A Parallelism Analyzer for Conservative Parallel Simulation
IEEE Transactions on Parallel and Distributed Systems
Parallelism in sequential multiprocessor simulation models: a case study
ACM Transactions on Modeling and Computer Simulation (TOMACS)
PADS '95 Proceedings of the ninth workshop on Parallel and distributed simulation
Estimating the benefit of the parallelisation of discrete event simulation
WSC '95 Proceedings of the 27th conference on Winter simulation
Conservative circuit simulation on shared-memory multiprocessors
PADS '96 Proceedings of the tenth workshop on Parallel and distributed simulation
A probabilistic event scheduling policy for optimistic parallel discrete event simulation
PADS '98 Proceedings of the twelfth workshop on Parallel and distributed simulation
Web-based simulation experiments
Proceedings of the 30th conference on Winter simulation
Performance Evaluation of Conservative Algorithms in Parallel Simulation Languages
IEEE Transactions on Parallel and Distributed Systems
Partitioning WCN models for parallel simulation of radio resource management
Wireless Networks - Special issue: Design and modeling in mobile and wireless systsems
Predicting the performance of synchronous discrete event simulation systems
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
Predicting the Performance of Synchronous Discrete Event Simulation
IEEE Transactions on Parallel and Distributed Systems
Optimistic Protocol Analysis in a Performance Analyzer and Prediction Tool
Proceedings of the 19th Workshop on Principles of Advanced and Distributed Simulation
Eliminating remote message passing in optimistic simulation
Proceedings of the 38th conference on Winter simulation
On the parallel simulation of scale-free networks
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation
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Discrete event simulation is usually time consuming. Recently, there has been a great deal of interest in using parallel computers to speed up the simulation process. Before the parallel simulation approach is applied, it is important to understand the inherent parallelism of simulation applications. A simple technique called critical path analysis was proposed to study paralllelism of simulation applications. This paper describes three critical path analysis algorithms based on different event-scheduling (process scheduling) policies. These algorithms are much simpler than a previous approach, where the events must be recorded in a trace and an extra pass is required to process the event trace. In our approach, the critical path analysis algorithms are integrated with the sequential simulation. At the end of the sequential simulation, the optimal parallel execution time is also computed. Livny proposed an algorithm similar to our approach (His, however, was designed for a specific language). Our algorithms can be integrated with sequential simulation programs written by users or be integrated with simulation languages. Another advantage of our algorithms over previous approaches is that ours can be used to study load balancing under different event-scheduling policies. Since our algorithms can be easily inserted in sequential simulation programs, critical path analysis can be applied to existing sequential programs without difficulty. The results can then be used to predict the performance of parallel simulation on similar applications. An example is given to show how useful information can be obtained from our algorithms.