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An Interactive Visual Tool for Code Optimization and Parallelization Based on the Polyhedral Model

机译:基于多面体模型的代码优化和并行化的交互式视觉工具

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Writing high performance software requires the programmer to take advantage of multi-core processing. This can be done through tools like OpenMP, which allow the programmer to mark parallel loops. Identifying parallelizable loops, however, is a non-trivial task. Furthermore, transformations can be applied to a loop nest to expose parallelism. Polyhedral compilation has become an increasingly popular technique for exposing parallelism in computationally intensive loop nests. These techniques can simultaneously optimize for a number of performance parameters (i.e. parallelism, locality, etc). This is typically done using a cost model designed to give good performance in the general case. For some problems, the compiler may miss optimization opportunities or even produce a transformation that leads to worse performance. In these cases, the user has little recourse, since there are few options for the user to affect the transformation decisions. In this paper we present PUMA-V, a visualization interface that helps the user understand and affect the transformations made by R-Stream, an industrial strength optimizing compiler based on the polyhedral model. This tool visualizes performance heuristics and runtime performance statistics to help the user identify missed optimization opportunities. Changes to the transformed code can be made by directly manipulating the visualizations. We show an example where performance is greatly improved over the polyhedral model alone by using our tool.
机译:编写高性能软件需要程序员利用多核处理。这可以通过像OpenMP这样的工具来完成,这允许程序员标记并行环路。然而,识别并行循环是非琐碎的任务。此外,可以将变换应用于循环嵌套以暴露并行性。多面体编译已成为在计算密集环巢中暴露平行性的越来越流行的技术。这些技术可以同时针对许多性能参数(即行性,地点等)进行优化。这通常是使用旨在在一般情况下提供良好性能的成本模型进行的。对于一些问题,编译器可能会错过优化机会,甚至会产生导致更糟糕的性能的转换。在这些情况下,用户的追索权很少,因为用户少量影响转换决策。在本文中,我们提出了Puma-V,一种可视化接口,可帮助用户理解并影响R流,基于多面体模型的工业强度优化编译器。此工具可视化性能启发式和运行时性能统计信息,以帮助用户识别错过的优化机会。可以通过直接操纵可视化来进行转换代码的更改。我们展示了一个例子,通过使用我们的工具,单独的性能大大提高了性能。

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