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Optimization techniques for concurrent STM-based implementations: A concurrent binary heap as a case study

机译:基于并发STM的实现的优化技术:以并发二进制堆为例

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Much research has been done in the area of software transactional memory (STM) as a new programming paradigm to help ease the implementation of parallel applications. While most research has been invested for answering the question of how STM should be implemented, there is less work about how to use STM efficiently. This paper is focused on the challenge of how to use STM for efficient and scalable implementations of non-trivial applications. We present a fine-grained STM-based concurrent binary heap, an application of STM for a data structure that is notoriously difficult to parallelize. We describe extensions to the basic STM approach and also the benefits of our proposal. Our results show that the fine-grained STM-based binary heap provides very good scalability compared to the naive approach. Nevertheless, we reach a point where the complexity of some fine-grained techniques do not justify its use for the increase in performance that can be obtained.
机译:作为新的编程范例,软件事务存储(STM)领域已进行了大量研究,以帮助简化并行应用程序的实现。尽管大多数研究已经投入用于回答应如何实施STM的问题,但有关如何有效使用STM的工作却很少。本文重点关注如何将STM用于非平凡应用程序的有效和可扩展实现的挑战。我们提出了一种基于STM的细粒度并发二进制堆,这是STM用于难以并行化的数据结构的应用。我们描述了对基本STM方法的扩展以及我们建议的好处。我们的结果表明,与朴素的方法相比,基于STM的细粒度二进制堆提供了很好的可伸缩性。但是,我们达到了某种程度,即某些细粒度技术的复杂性无法证明其可用于提高性能的合理性。

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