增强超并发的最优选择理论

Mu-Cheng Wang, Shin-Dug Kim, M. A. Nichols, R. F. Freund, H. Siegel, W. Nation
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引用次数: 66

摘要

提出了一种异构计算机系统优化配置解决超级计算问题的方法。超并发作为分布式异构超级计算的一种形式,是一种匹配和管理一组最佳配置的超高速计算机的方法,以最大限度地减少给定任务的执行时间。当一组给定任务的计算需求不同时,该方法的性能最好。将一个超级计算应用任务分解为一组代码段,每个代码段的处理需求是同构的。提出了最优选择理论,用于选择超级计算问题中机器的最优配置。该技术基于代码分析和分析基准测试。本文从两个方面对先前提出的最优选择理论方法进行了扩充:一是考虑了码段在非最优机器选择上的性能,二是考虑了码段的非均匀性和组合性。
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Augmenting the Optimal Selection Theory for Superconcurrency
An approach for jinding the optimal configuration of heterogeneous computer systems to solve supercomputing problem is presented. Superconcurrency as a form of distributed heterogeneous supercomputing is an approach for matching and managing an optimally configured suite of super-speed machines to minimize the execution time on a given task. The approach performs best when the computational requirements for a given set of tasks are diverse. A supercomputing application task is decomposed into a collection of code segments, where the processing requirement is homogeneous in each code segment. The optimal selection theory has been proposed to choose the optimal configuration of machines for a supercomputing problem. This technique is based on code projiling and analytical benchmarking. Here, the previously presented optimal selection theory approach is augmented in two ways: the performance of code segments on non-optimal machine choices is incorporated and non-uniform &compositions of code segments are considered.
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