面向数组私有化和程序并行化的符号数组数据流分析

Junjie Gu, Zhiyuan Li, Gyungho Lee
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引用次数: 61

摘要

数组数据流信息对Fortran程序的自动并行化起着重要的作用。本文提出了一种强大的符号数组数据流分析方法,以支持任意控制流图和非循环调用图程序的数组私有化和循环并行化。我们的方案使用保护数组区域总结数组访问信息,并在分层超图(HSG)上传播这些区域。使用警卫使我们能够使用中频条件下的信息来锐化阵列数据流分析,从而处理其他现有技术无法处理的困难情况。保护数组区域在一般情况下保留了常规数组区域集合操作的简单性,在复杂情况下通过使用保护来处理复杂的符号表达式和数组形状,增强了常规数组区域。出现在数组下标和循环限制中的标量值在数组信息传播期间被动态替换,从而精确地消除了用于集合操作的符号值的歧义。我们提出了有效的算法来实现我们的方案。将我们的分析应用于Perfect benchmark的初步实验显示了改进阵列私有化的有希望的结果。
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Symbolic Array Dataflow Analysis for Array Privatization and Program Parallelization
Array dataflow information plays an important role for successful automatic parallelization of Fortran programs. This paper proposes a powerful symbolic array dataflow analysis to support array privatization and loop parallelization for programs with arbitrary control flow graphs and acyclic call graphs. Our scheme summarizes array access information using guarded array regions and propagates such regions over a Hierarchical Supergraph (HSG). The use of guards allows us to use the information in IF conditions to sharpen the array dataflow analysis and thereby to handle difficult cases which elude other existing techniques. The guarded array regions retain the simplicity of set operations for regular array regions in common cases, and they enhance regular array regions in complicated cases by using guards to handle complex symbolic expressions and array shapes. Scalar values that appear in array subscripts and loop limits are substituted on the fly during the array information propagation, which disambiguates the symbolic values precisely for set operations. We present efficient algorithms that implement our scheme. Initial experiments of applying our analysis to Perfect Benchmarks show promising results of improved array privatization.
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