Publication | Closed Access
Comparative analysis of periodic state saving techniques in time warp simulators
64
Citations
10
References
2002
Year
Unknown Venue
Cluster ComputingEngineeringComputer ArchitectureCheckpoint IntervalsSimulationClock SynchronizationDiscrete-event SimulationStabilityTime Warp SimulatorsTiming AnalysisParallel SimulatorSystems EngineeringFault RecoveryModeling And SimulationParallel ComputingComparative AnalysisTimed SystemNonlinear Time SeriesPeriodic StateComputer EngineeringLarge-scale SimulationSpace-time SimulationComputer ScienceReal-time SimulationTime Warp SimulatorSoftware TestingParallel Programming
Checkpointing in a time warp synchronized parallel simulator is a necessary and potentially expensive operation. In the simple case, a time warp simulator checkpoints every /spl chi/ events, for some fired value /spl chi/. For larger values of /spl chi/, the simulator requires less overhead for saving the state, but incurs an increased latency during rollback. Thus, the problem is to balance the time to save states against the time to coast forward upon rollback. Unfortunately, a static determination of an optimal value for /spl chi/ is very difficult and can vary widely, even between closely related instances of a time warp simulator. Furthermore, the optimal checkpoint interval may actually vary over the lifetime of the simulation. To address these problems, several investigators have proposed dynamically adjusting the checkpoint interval /spl chi/ as the simulation progresses. This paper analyzes three previous techniques for dynamically sizing checkpoint intervals and presents a new, heuristic algorithm for this purpose. All four techniques are implemented in a common application domain (digital system simulation from VHDL descriptions) and a direct comparison between the algorithms is performed. The results show a significant difference in the performance of the implemented algorithms. However, in virtually all cases, the dynamic algorithms performed near or better than the best static value. Furthermore, the best algorithms performed as much as 12% better than the best static value.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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