Brief Announcement: Dynamic Determinacy Race Detection for Task Parallelism with Futures

R. Surendran, Vivek Sarkar
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引用次数: 3

Abstract

Existing dynamic determinacy race detectors for task-parallel programs are limited to programs with strict computation graphs, where a task can only wait for its descendant tasks to complete. In this paper, we present the first known determinacy race detector for non-strict computation graphs with futures. The space and time complexity of our algorithm are similar to those of the classical SP-bags algorithm, when using only structured parallel constructs such as spawn-sync and async-finish. In the presence of point-to-point synchronization using futures, the complexity of the algorithm increases by a factor determined by the number of future operations, which includes future task creation and future get operations. The experimental results show that the slowdown factor observed for our algorithm relative to the sequential version is in the range of 1.00x to 9.92x, which is very much in line with slowdowns experienced for fully strict computation graphs.
简要公告:动态确定性竞争检测与未来任务并行
现有用于任务并行程序的动态确定性竞争检测器仅限于具有严格计算图的程序,其中任务只能等待其后代任务完成。在本文中,我们提出了已知的第一个具有期货的非严格计算图的确定性竞争检测器。当只使用结构化并行结构(如spawn-sync和async-finish)时,我们算法的空间和时间复杂度与经典SP-bags算法相似。在使用future的点对点同步中,算法的复杂性增加了一个因子,该因子由未来操作的数量决定,其中包括未来的任务创建和未来的get操作。实验结果表明,相对于顺序版本,我们的算法观察到的减速因子在1.00x到9.92x的范围内,这与完全严格计算图的减速非常一致。
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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