Implementations and Evaluations of Non-numerical Algorithms for MIMD Multiprocessors

目前市面上的多处理器超级计算机都是面向高速数值计算的。然而，现在更倾向于使用计算机进行本质上具有象征意义的计算。多处理器的非数值算法比数值算法更难设计和评估。本研究旨在开发一种新的集成方法，用于多处理器非数值并行和分布式算法的设计和性能预测。由于这种算法的不可预测行为，以及算法性能对数据值的依赖性，模拟是该方法的基本组成部分。为在单处理器上模拟多处理器算法的执行而开发的设施将被扩展、改进和调整到本研究的目的。这个模拟器是跟踪驱动的。模拟结果将用于验证现有的或新的分析或混合建模技术。

Multiprocessor supercomputers presently available on the market are oriented towards high-speed numerical computation. However, there is more tendency to use computers for computations that are symbolic in nature. Nonnumerical algorithms for multiprocessors are more difficult to design and evaluate than numerical algorithms. This research is aimed at developing a new and integrated methodology for the design and performance prediction of nonnumerical parallel and distributed algorithms for multiprocessors. Because of the unpredictable behavior of such algorithms, and the dependency of algorithm performance on data values, simulation is a fundamental ingredient of the methodology. The facility developed for simulating the execution of multiprocessor algorithms on uniprocessors will be expanded, improved and tuned to the purpose of this research. This simulator is trace-driven. Simulation results will be used to validate existing or new analytical or hybrid modeling techniques.