延迟分解:一种控制并行任务粒度的新技术

Suntae Hwang, H. Cha
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引用次数: 0

摘要

本文介绍了一种新的大晶粒平行曝光机制。该方案执行延迟任务创建;暂时内联所有任务,然后根据需要从内联信息中提取并行性。然而,与其他机制不同的是,进一步的任务需求由下一个评估流来满足,而不是回顾性地逆转当前流的内联决策。该方案被称为惰性分解,因为分解本身是受限的,而不仅仅是任务的提取。惰性分解使得串行部分在特定函数的求值树中与并行部分明显分离,这允许串行部分采用顺序算法。在分而治之的应用中,采用顺序算法可以显著提高性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lazy decomposition: a novel technique to control parallel task granularity
This paper introduces a new mechanism for the exposure of large grain parallelism. The scheme performs lazy task creation; inlining all tasks provisionally and extracting parallelism from the inlined information later on demand. However, unlike other mechanisms, the further task demand is satisfied by the next evaluation stream rather than retrospectively reversing the inlining decision of the current stream. The scheme is called lazy decomposition because decomposition itself is throttled rather than just the extraction of a task. Lazy decomposition makes the serial section clearly separated from the parallel section in an evaluation tree for a particular function, and this allows the serial section to adopt a sequential algorithm. The performance improvement is significant in divide-and-conquer applications by adoption of sequential algorithms.
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