Idiom Recognition and Program Scheme Recognition Based Program Transformations for Performance Tuning--Beyond Compiler Optimizations--

S. Hiroyuki
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引用次数: 1

Abstract

Much effort has been performed for performance tuning. However, it is becoming clear that performance tuning is much harder in complicated modern parallel architectures. For performance tuning, compiler approach was prevailing in the era of vector architecture. Today, instead, PSE approach which provides users with abstract programming emerges, which also has a problem in tuning fine points. Another approach is “ autotuning” which is a brute force attack for performance tuning. We have proposed that idiom recognition can be a bridge between abstract source programs and concrete architectures. This paper applies term rewriting theory -a very general framework to the idiom recognition system. Moreover, we apply higher order term rewriting to find better patterns. We show that tiling and recursive algorithm scheme patterns can be reinvented by the extended idiom recognition. Furthermore, we discuss a method of enrichment of candidates of optimizations by using the general framework of graph rewriting.
基于习惯用法识别和程序方案识别的程序转换,用于性能调优——超越编译器优化
在性能调优方面已经做了很多工作。然而,越来越明显的是,在复杂的现代并行体系结构中,性能调优要困难得多。对于性能调优,编译器方法在矢量架构时代盛行。而现在,为用户提供抽象编程的PSE方法出现了,它在微调点方面也存在问题。另一种方法是“自动调优”,这是一种针对性能调优的暴力攻击。我们已经提出习语识别可以成为抽象源程序和具体体系结构之间的桥梁。本文将术语改写理论这一非常通用的框架应用到习语识别系统中。此外,我们应用高阶项重写来找到更好的模式。通过扩展成语识别,我们证明了平铺和递归算法模式可以被重新发明。此外,我们还讨论了一种利用图重写的一般框架来丰富优化候选项的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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