求解SAT混合并行执行的理论研究

International congress series Pub Date : 2007-07-01 DOI:10.1016/j.ics.2006.12.021

Kairong Zhang , Masahiro Nagamatu

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引用次数: 3

摘要

对于可满足性问题(SAT)，我们提出了一种称为LPPH的神经网络和一种称为“混合并行执行”的并行化方法，其中LPPH和其他算法同时执行。本文研究了混合并行执行的CPU时间，证明了并行执行中所用算法的CPU时间分布函数之间的差异越大，混合并行执行的效率越高。

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Theoretical study on mixed parallel execution for solving SAT

For the satisfiability problem (SAT), we have proposed a neural network, called LPPH, and a parallelization method, called “mixed parallel execution,” in which LPPH and other algorithms are executed simultaneously. In this paper we study the CPU time of the mixed parallel execution, and prove that the bigger the difference between distribution functions of CPU time of the algorithms used in the parallel execution, the more effective the mixed parallel execution is.

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International congress series

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