In a distributed memory environment the communication overhead of Time Warp is the dominating performance factor. In order to limit the optimism to the extent that can be justified from the inherent model parallelism,...
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In a distributed memory environment the communication overhead of Time Warp is the dominating performance factor. In order to limit the optimism to the extent that can be justified from the inherent model parallelism, an optimism control mechanism is proposed. After investigating statistical forecast methods, it is shown that arrival processes in the context of Time Warp simulations of timed Petri nets have certain predictable and consistent ARIMA characteristics.
The implementation of a distributed digital logic simulation algorithm on a network of workstations is presented. The simulation of digital circuits is done using a demand driven approach. The simulation is performed ...
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Performance of Time Warp simulation systems are often measured on exclusively available parallel computing resources. In distributed systems exclusive use is normally not feasible. Instead, due to the multi-tasking op...
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Performance of Time Warp simulation systems are often measured on exclusively available parallel computing resources. In distributed systems exclusive use is normally not feasible. Instead, due to the multi-tasking operating systems, many users share the workstations and their availability for parallelsimulation purposes varies extensively. Time Warp has been found to be very sensitive to variations in available processing power. This paper presents two methods for a Time Warp VLSI simulation system to reduce the negative effect of a non-ideal environment on the execution of parallelsimulations. A dynamic load balancing algorithm which adapts to the change of available processing power is presented. This mechanism, together with a multi-cluster partitioning technique significantly improves the performance of Time Warp based simulation systems on heterogeneous computing resources.
The partitioning of systems for parallelsimulation is a complex task, requiring consideration of both computational load requirements and communications activity. Typically, this information is not accurately known p...
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The partitioning of systems for parallelsimulation 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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