跨并行语言和体系结构的NAS MG基准比较研究

B. Chamberlain, Steven J. Deitz, L. Snyder
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引用次数: 60

摘要

分层算法如多网格应用构成了科学计算的重要基石。在这项研究中,我们通过比较几种并行编程语言(Co-Array Fortran、High Performance Fortran、Single Assignment C和ZPL)对NAS MG基准的实现,迈出了评估并行语言对分层应用程序支持的第一步。我们根据可移植性、性能以及清晰简洁地表达算法的能力来评估每种语言。实验平台包括Cray T3E、IBM SP、SGI Origin、Sun Enterprise 5500和一个高性能Linux集群。我们的研究结果表明,虽然有可能实现良好的可移植性、性能和表达性,但大多数语言目前至少在这些领域中的一个方面存在不足。我们发现表达性和语言对计算全局视图的支持之间存在很强的相关性,并且我们确定了在多网格应用程序中实现可移植性能的关键因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comparative Study of the NAS MG Benchmark across Parallel Languages and Architectures
Hierarchical algorithms such as multigrid applications form an important cornerstone for scientific computing. In this study, we take a first step toward evaluating parallel language support for hierarchical applications by comparing implementations of the NAS MG benchmark in several parallel programming languages: Co-Array Fortran, High Performance Fortran, Single Assignment C, and ZPL. We evaluate each language in terms of its portability, its performance, and its ability to express the algorithm clearly and concisely. Experimental platforms include the Cray T3E, IBM SP, SGI Origin, Sun Enterprise 5500, and a high-performance Linux cluster. Our findings indicate that while it is possible to achieve good portability, performance, and expressiveness, most languages currently fall short in at least one of these areas. We find a strong correlation between expressiveness and a language’s support for a global view of computation, and we identify key factors for achieving portable performance in multigrid applications.
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