灵活的基于引用计数的垃圾收集硬件加速

José A. Joao, O. Mutlu, Y. Patt
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引用次数: 44

摘要

具有自动内存管理(垃圾收集)特性的语言越来越多地用于编写各种应用程序,因为它们提供了明显的软件工程和安全优势。不幸的是,垃圾收集会对性能造成影响,并引入暂停时间,使此类语言对高性能或实时应用程序的吸引力降低。在过去的50年里,在减少垃圾收集的开销方面已经取得了很大的进展,但它仍然很重要。我们提出了一种软硬件协同技术来降低垃圾回收的性能开销。其关键思想是通过硬件实现的引用计数来有效地检测和重用硬件中的死内存空间,从而减少垃圾收集的频率。因此,即使最终仍然需要软件垃圾收集,它们也变得不那么频繁,对整体性能的影响也更小。我们的技术与各种软件垃圾收集算法兼容,不会破坏与现有软件的兼容性,并且在Jikes RVM的生产构建上运行的Java DaCapo基准测试中平均减少了31%的垃圾收集时间,Jikes RVM使用了最先进的分代垃圾收集器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flexible reference-counting-based hardware acceleration for garbage collection
Languages featuring automatic memory management (garbage collection) are increasingly used to write all kinds of applications because they provide clear software engineering and security advantages. Unfortunately, garbage collection imposes a toll on performance and introduces pause times, making such languages less attractive for high-performance or real-time applications. Much progress has been made over the last five decades to reduce the overhead of garbage collection, but it remains significant. We propose a cooperative hardware-software technique to reduce the performance overhead of garbage collection. The key idea is to reduce the frequency of garbage collection by efficiently detecting and reusing dead memory space in hardware via hardware-implemented reference counting. Thus, even though software garbage collections are still eventually needed, they become much less frequent and have less impact on overall performance. Our technique is compatible with a variety of software garbage collection algorithms, does not break compatibility with existing software, and reduces garbage collection time by 31% on average on the Java DaCapo benchmarks running on the production build of the Jikes RVM, which uses a state-of-the-art generational garbage collector.
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