Abstract
The partitioning of systems for parallel simulation is a complex task, requiring consideration of both computational load requirements and communications activity. Typically, this information is not accurately known prior to execution. This paper investigates the use of historical information for the prediction of future requirements, both for computation and communications. In addition, for optimistic simulation algorithms, we present a novel technique (which we call predictive optimism) whereby binary prediction schemes can be used to increase the accuracy of optimistic assumptions, thereby decreasing rollbacks and potentially improving overall simulator performance.
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