2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation (1995)
Lake Placid, New York
June 14, 1995 to June 16, 1995
A. Ferscha , Inst. fur Angewandte Inf., Wien Univ., Austria
In a distributed memory environment the communication overhead of Time Warp as induced by the rollback procedure due to "overoptimistic" progression of the simulation is the dominating performance factor. To limit optimism to an extent that can be justified from the inherent model parallelism, an optimism control mechanism is proposed, which by maintaining a history record of virtual time differences from the time stamps carried by arriving messages, and forecasting the timestamps of forthcoming messages, probabilistically delays the execution of scheduled events to avoid potential rollback and associated communication overhead (antimessages). After investigating statistical forecast methods which express only the central tendency of the arrival process, we demonstrate that arrival processes in the context of Time Warp simulations of timed Petri nets have certain predictable and consistent ARIMA characteristics, which encourage the use of sophisticated and recursive forecast procedures based on those models. Adaptiveness is achieved in two respects: the synchronization behavior of logical processes automatically adjusts to that point in the continuum between optimistically progressing and conservatively blocking, that is the most adequate for (i) the specific simulation model and (ii) the communication/computation speed characteristics of the underlying execution platform.
time warp simulation; delays; Petri nets; synchronisation; probabilistic adaptive direct optimism control; time warp simulation; distributed memory environment; communication overhead; rollback procedure; inherent model parallelism; optimism control mechanism; timed Petri nets; ARIMA characteristics; synchronization behavior
A. Ferscha, "Probabilistic adaptive direct optimism control in time warp", 2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation, vol. 00, no. , pp. 120, 1995, doi:10.1109/PADS.1995.404309