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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, the authors 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, they present a probabilistic synchronization scheme that obtains extensive knowledge of the simulation behavior at runtime to guide event execution.
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