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arXiv 1902.07660cs.DScs.CC
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高效并行参数化算法

Towards Work-Efficient Parallel Parameterized Algorithms

Max Bannach, Malte Skambath, Till Tantau

摘要:

并行参数化复杂性理论研究如何并行求解固定参数易处理问题。以前的理论工作集中在原则上非常快的并行算法上,但没有考虑到当我们只有少量处理器(在2到1024之间)时,更重要的是并行算法的工作效率。在本文中,我们研究如何工作效率的fpt算法可以设计。我们回顾了fpt理论中的标准方法,如核化,搜索树和交织,并证明了它们在工作效率和运行时改进之间的权衡。这就产生了一个开发高效并行fpt算法的工具箱。

英文摘要:

Parallel parameterized complexity theory studies how fixed-parameter tractable (fpt) problems can be solved in parallel. Previous theoretical work focused on parallel algorithms that are very fast in principle, but did not take into account that when we only have a small number of processors (between 2 and, say, 1024), it is more important that the parallel algorithms are work-efficient. In the present paper we investigate how work-efficient fpt algorithms can be designed. We review standard methods from fpt theory, like kernelization, search trees, and interleaving, and prove trade-offs for them between work efficiency and runtime improvements. This results in a toolbox for developing work-efficient parallel fpt algorithms.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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