A framework for performance analysis of parallel discrete event simulators
Proceedings of the 29th conference on Winter simulation
Early cancellation: an active NIC optimization for time-warp
Proceedings of the sixteenth workshop on Parallel and distributed simulation
Parallel Synchronization of Continuous Time Discrete Event Simulators
ICPP '97 Proceedings of the international Conference on Parallel Processing
Using Programmable NICs for Time-Warp Optimization
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
A Comparative Analysis of Various Time Warp Algorithms Implemented in the WARPED Simulation Kernel
SS '96 Proceedings of the 29th Annual Simulation Symposium (SS '96)
On constructing optimistic simulation algorithms for the discrete event system specification
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Event pool structures for PDES on many-core Beowulf clusters
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation
| Hi-index | 0.00 |
The performance of a Time Warp parallel discrete event simulator (PDES) depends on the efficiency of the cancellation strategy employed to undo the effects of the erroneous computation. Two known cancellation strategies exist, namely aggressive cancellation and lazy cancellation. Under aggressive cancellation (AC), when a straggler arrives at a logical process (LP), it rolls back to an appropriate previous state and immediately sends out anti messages for all the messages that were processed prematurely. In contrast, under lazy cancellation (LC), the anti messages are delayed until forward processing demonstrates that the originally sent output messages were incorrect. The performance under LC deteriorates if the probability of the regenerated output messages being different from the originally sent messages, is high. AC, on the other hand, performs badly if the same messages are generated before and after a rollback most of the time. In general, it has proven to be difficult to determine a priori the favorable cancellation strategy. Thus, we propose that the performance of a Time Warp simulator is best optimized by having the simulation dynamically select the cancellation strategy to be used based on the behavior of the application being simulated. A simple approach to achieve this is based on a parameter called the hit/miss ratio. The results obtained using this adaptive approach are compared with the results obtained using only aggressive cancellation or lazy cancellation. These results show that for our application, digital system simulation, the adaptive technique works better than either cancellation strategy.