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From Sequential to Parallel Local Search for SAT

机译:从顺序搜索到并行本地搜索SAT

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摘要

In the domain of propositional Satisfiability Problem (SAT), parallel portfolio-based algorithms have become a standard methodology for both complete and incomplete solvers. In this methodology several algorithms explore the search space in parallel, either independently or cooperatively with some communication between the solvers. We conducted a study of the scalability of several SAT solvers in different application domains (crafted, verification, quasigroups and random instances) when drastically increasing the number of cores in the portfolio, up to 512 cores. Our experiments show that on different problem families the behaviors of different solvers vary greatly. We present an empirical study that suggests that the best sequential solver is not necessary the one with the overall best parallel speedup.
机译:在命题可满足性问题(SAT)的领域中,基于投资组合的并行算法已成为完整和不完整求解器的标准方法。在这种方法中,几种算法可以并行或独立地或与求解器之间的某些通信协作地探索搜索空间。当大幅增加投资组合中的核心数量(最多512个核心)时,我们对不同应用程序域中的几个SAT求解器的可伸缩性进行了研究(精心设计,验证,拟群和随机实例)。我们的实验表明,在不同的问题系列上,不同求解器的行为差异很大。我们提出了一项实证研究,表明最佳的顺序求解器不一定是总体上最佳并行加速器。

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