Trade-Off between Sequential and Time Warp-Based Parallel Simulation

Discrete event simulation is a methodology to study the behavior of complex systems. Its drawback is that, in order to get reliable results, simulations usually have to be run over a long stretch of time. This time requirement could decrease through the usage of parallel or distributed computing systems. In this paper, we analyze the Time Warp synchronization protocol for parallel discrete event simulation and present an analytical model evaluating the upper bound on the completion time of a Time Warp simulation. In our analysis, we consider the case of a simulation model with homogeneous logical processes, where "homogeneous" means they have the same average event routine time and the same state saving cost. Then we propose a methodology to determine when it is time-convenient to use a Time Warp synchronized simulation, instead of a sequential one, for a simulation model with features matching those considered in our analysis. We give an answer to this question without the need to preliminary generate the simulation code. Examples of methodology usage are reported for the case of both a synthetic benchmark and a real world model.

[1]  Rassul Ayani,et al.  Adaptive checkpointing in Time Warp , 1994, PADS '94.

[2]  David R. Jefferson,et al.  Virtual time , 1985, ICPP.

[3]  John G. Cleary,et al.  An external state management system for optimistic parallel simulation , 1993, WSC '93.

[4]  Leonard Kleinrock,et al.  Bounds and approximations for self-initiating distributed simulation without lookahead , 1991, TOMC.

[5]  Theodore R. Bashkow,et al.  A large scale, homogeneous, fully distributed parallel machine, I , 1977, ISCA '77.

[6]  Albert G. Greenberg,et al.  Synchronous relaxation for parallel simulations with applications to circuit-switched networks , 1993, TOMC.

[7]  Stephen S. Lavenberg,et al.  Performance Analysis of a Rollback Method for Distributed Simulation , 1983, International Symposium on Computer Modeling, Measurement and Evaluation.

[8]  Jayadev Misra,et al.  Distributed discrete-event simulation , 1986, CSUR.

[9]  K. Mani Chandy,et al.  Distributed Simulation: A Case Study in Design and Verification of Distributed Programs , 1979, IEEE Transactions on Software Engineering.

[10]  J. Steinman,et al.  SPEEDES: Synchronous Parallel Environment for Emulation and Discrete-Event Simulation , 1991 .

[11]  Alois Ferscha,et al.  Estimating rollback overhead for optimism control in Time Warp , 1995, Proceedings of Simulation Symposium.

[12]  R. M. Fujimoto,et al.  Parallel discrete event simulation , 1989, WSC '89.

[13]  Yi-Bing Lin,et al.  Selecting the checkpoint interval in time warp simulation , 1993, PADS '93.

[14]  David Jefferson,et al.  Fast Concurrent Simulation Using the Time Warp Mechanism. Part I. Local Control. , 1982 .

[15]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[16]  Ronald J. Watro,et al.  Mathematical foundations for time warp systems , 1993, TOPL.

[17]  K. Mani Chandy,et al.  A Message-Based Approach to Discrete-Event Simulation , 1987, IEEE Transactions on Software Engineering.

[18]  David M. Nicol,et al.  Performance bounds on parallel self-initiating discrete-event simulations , 1990, TOMC.

[19]  Alois Ferscha Probabilistic adaptive direct optimism control in Time Warp , 1995, PADS.

[20]  Yi-Bing Lin,et al.  A Parallelism Analyzer for Conservative Parallel Simulation , 1995, IEEE Trans. Parallel Distributed Syst..

[21]  A. Ferscha Probabilistic adaptive direct optimism control in time warp , 1995, Proceedings 9th Workshop on Parallel and Distributed Simulation (ACM/IEEE).

[22]  Isi Mitrani,et al.  Analysis and Optimum Performance of Two Message-Passing Parallel Processors Synchronized by Rollback , 1984, Perform. Evaluation.

[23]  Satish K. Tripathi,et al.  Performance Analysis of Synchronization for Two Communicating Processes , 1988, Perform. Evaluation.

[24]  Ian F. Akyildiz,et al.  Performance Analysis of Time Warp With Multiple Homogeneous Processors , 1991, IEEE Trans. Software Eng..

[25]  Herbert Bauer,et al.  Reducing Rollback Overhead In Time-warp Based Distributed Simulation With Optimized Incremental State Saving , 1993, [1993] Proceedings 26th Annual Simulation Symposium.

[26]  Ganesh Gopalakrishnan,et al.  Design and Evaluation of the Rollback Chip: Special Purpose Hardware for Time Warp , 1992, IEEE Trans. Computers.

[27]  Philip A. Wilsey,et al.  An analytical comparison of periodic checkpointing and incremental state saving , 1993, PADS '93.

[28]  Vaidy S. Sunderam,et al.  PVM: A Framework for Parallel Distributed Computing , 1990, Concurr. Pract. Exp..

[29]  David M. Nicol,et al.  Analysis of bounded time warp and comparison with YAWNS , 1996, TOMC.

[30]  Hassan Rajaei,et al.  Parallel simulation using conservative time windows , 1992, WSC '92.

[31]  Yi-Bing Lin,et al.  Optimality considerations of 'Time Warp' parallel simulation , 1990 .

[32]  K M Chandy,et al.  The Conditional-Event Approach to Distributed Simulation , 1989 .

[33]  Carl Tropper,et al.  On Process Migration and Load Balancing in Time Warp , 1993, IEEE Trans. Parallel Distributed Syst..