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<p>Design and development costs for extremely large systems could be significantly reduced if only there were efficient techniques for evaluating design alternatives and predicting their impact on overall system performance metrics. Due to the systems' analytical intractability, simulation is the most common performance evaluation technique for such systems. However, the long execution times needed for sequential simulation models often hampers evaluation. </p> <p>The slow speeds of sequential model execution have led to growing interest in the use of parallel execution for simulating large-scale systems. Widespread use of parallel simulation, however, has been significantly hindered by a lack of tools for integrating parallel model execution into the overall framework of system simulation. Another drawback to wide-spread use of simulations is the cost of model design and maintenance. </p> <p>The simulation environment the authors developed at UCLA attempts to address some of these issues. It consists of three primary components: a parallel simulation language called Parsec (parallel simulation environment for complex systems), its GUI, called Pave, and the portable runtime system that implements the simulation algorithms. </p>

Y. Chen et al., "Parsec: A Parallel Simulation Environment for Complex Systems," in Computer, vol. 31, no. , pp. 77-85, 1998.
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