Fifth International Conference on Simulation Tools and Techniques

Research Article

Know Thy Simulation Model: Analyzing Event Interactions for Probabilistic Synchronization in Parallel Simulations

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  • @INPROCEEDINGS{10.4108/icst.simutools.2012.247716,
        author={Georg Kunz and Mirko Stoffers and James Gross and Klaus Wehrle},
        title={Know Thy Simulation Model: Analyzing Event Interactions for Probabilistic Synchronization in Parallel Simulations},
        proceedings={Fifth International Conference on Simulation Tools and Techniques},
        publisher={ICST},
        proceedings_a={SIMUTOOLS},
        year={2012},
        month={6},
        keywords={parallel network simulation probabilistic synchronization},
        doi={10.4108/icst.simutools.2012.247716}
    }
    
  • Georg Kunz
    Mirko Stoffers
    James Gross
    Klaus Wehrle
    Year: 2012
    Know Thy Simulation Model: Analyzing Event Interactions for Probabilistic Synchronization in Parallel Simulations
    SIMUTOOLS
    ICST
    DOI: 10.4108/icst.simutools.2012.247716
Georg Kunz1,*, Mirko Stoffers1, James Gross1, Klaus Wehrle1
  • 1: RWTH Aachen University
*Contact email: kunz@comsys.rwth-aachen.de

Abstract

Efficiently scheduling and synchronizing parallel event execution constitutes the fundamental challenge in parallel discrete event simulation. Existing synchronization algorithms typically do not analyze event interactions within the simulation model – mainly to minimize runtime overhead and complexity. However, we argue that disregarding event interactions results in a lack of insight into the behavior of the simulation model, thereby severely limiting synchronization efficiency and thus parallel performance. In this paper, we present a probabilistic synchronization scheme that obtains extensive knowledge of the simulation behavior at runtime to guide event execution. Specifically, we design three heuristics that dynamically derive event dependencies from tracing event interactions and decide whether or not to speculatively execute events. Our evaluation shows that the proposed probabilistic synchronization scheme considerably outperforms traditional conservative and optimistic schemes.