Analysis of pure methods using garbage collection

Erik Österlund, Welf Löwe
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引用次数: 2

Abstract

Parallelization and other optimizations often depend on static dependence analysis. This approach requires methods to be independent regardless of the input data, which is not always the case. Our contribution is a dynamic analysis "guessing" if methods are pure, i. e., if they do not change state. The analysis is piggybacking on a garbage collector, more specifically, a concurrent, replicating garbage collector. It guesses whether objects are immutable by looking at actual mutations observed by the garbage collector. The analysis is essentially for free. In fact, our concurrent garbage collector including analysis outperforms Boehm's stop-the-world collector (without any analysis), as we show in experiments. Moreover, false guesses can be rolled back efficiently. The results can be used for just-in-time parallelization allowing an automatic parallelization of methods that are pure over certain periods of time. Hence, compared to parallelization based on static dependence analysis, more programs potentially benefit from parallelization.
分析使用垃圾回收的纯方法
并行化和其他优化通常依赖于静态依赖分析。这种方法要求无论输入数据如何,方法都是独立的,但情况并非总是如此。我们的贡献是动态分析,“猜测”方法是否纯粹,也就是说,如果它们不改变状态。该分析依赖于一个垃圾收集器,更具体地说,是一个并发的、复制的垃圾收集器。它通过查看垃圾收集器观察到的实际变化来猜测对象是否不可变。分析基本上是免费的。事实上,我们包含分析的并发垃圾收集器优于Boehm的stop-the-world收集器(没有任何分析),正如我们在实验中所展示的那样。此外,错误的猜测可以有效地回滚。结果可用于实时并行化,允许在特定时间段内对纯方法进行自动并行化。因此,与基于静态依赖分析的并行化相比,更多的程序可能受益于并行化。
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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