性能驱动的编程模型

W. Gropp
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引用次数: 1

摘要

大多数高性能、大规模并行处理器(mpp)的预测都包括深度和复杂的内存层次结构。要想有效地利用这些系统,就需要在不牺牲算法进步的前提下,有效地利用这些内存层次结构。为矢量计算机开发了高效的编程模型,特别是存储系统结构,提供了高性能。mpp的编程模型在哪里?人们在自动编程系统上投入了大量精力,例如为现有语言和表示并发性的新语言并行化编译器。不幸的是,这些很少导致程序能够达到接近峰值的性能。在本文中,我们回顾了这些问题和一些目前的方法,并提出了一些新的面向内存的编程模型。这些模型的发展是必不可少的,因为就像矢量计算一样,编程模型可以强烈地影响大规模并行处理器上高性能应用程序所需的新算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance driven programmimg models
Most projections for high-performance, massively parallel processors (MPPs) include deep and complex memory hierarchies. Making efficient use of these systems will require making efficient use of these memory hierarchies, without sacrificing the advancements that have been made in algorithms. Efficient programming models were developed for vector computers, particularly the memory system structure, providing high performance. Where are the programming models for MPPs? Much effort has gone into automatic programming systems, such as parallelizing compilers for existing languages and new languages expressing concurrency. Unfortunately, these have rarely led to programs that can achieve near-peak performance. In this paper, we review the issues and some current approaches and suggest some new memory-oriented programming models. The development of these models is essential, because, just as with vector computing, the programming model can strongly influence the new algorithms that are needed for high-performance applications on massively parallel processors.
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