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Loop Quasi-Invariant Chunk Motion by peeling with statement composition

机译:Loop Quasi-Invariant Chunk motion通过语句组合剥离

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摘要

Several techniques for analysis and transformations are used in compilers.Among them, the peeling of loops for hoisting quasi-invariants can be used tooptimize generated code, or simply ease developers' lives. In this paper, weintroduce a new concept of dependency analysis borrowed from the field ofImplicit Computational Complexity (ICC), allowing to work with composedstatements called Chunks to detect more quasi-invariants. Based on anoptimization idea given on a WHILE language, we provide a transformation method- reusing ICC concepts and techniques - to compilers. This new analysiscomputes an invariance degree for each statement or chunks of statements bybuilding a new kind of dependency graph, finds the maximum or worst dependencygraph for loops, and recognizes if an entire block is Quasi-Invariant or not.This block could be an inner loop, and in that case the computationalcomplexity of the overall program can be decreased. We already implemented aproof of concept on a toy C parser 1 analysing and transforming the ASTrepresentation. In this paper, we introduce the theory around this concept andpresent a prototype analysis pass implemented on LLVM. In a very near future,we will implement the corresponding transformation and provide benchmarkscomparisons.
机译:编译器使用了多种分析和转换技术,其中,用于提升准不变式的循环剥皮可用于优化生成的代码或简化开发人员的工作。在本文中,我们引入了一种从隐式计算复杂性(ICC)领域借来的依赖分析的新概念,从而允许与称为“块”的组合语句一起使用以检测更多的准不变性。基于WHILE语言给出的优化思想,我们为编译器提供了一种重用ICC概念和技术的转换方法。这项新的分析通过构建一种新的依赖图来计算每个语句或语句块的不变程度,找到循环的最大或最差依赖图,并识别整个块是否为准不变这个块可能是内部循环,在这种情况下,可以降低整个程序的计算复杂度。我们已经在玩具C解析器1上实现了概念验证,以分析和转换ASTrepresentation。在本文中,我们将介绍围绕该概念的理论,并介绍在LLVM上实现的原型分析过程。在不久的将来,我们将进行相应的转换并提供基准比较。

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