Exploiting hypergraph partitioning for efficient Boolean satisfiability

Proceedings. Ninth IEEE International High-Level Design Validation and Test Workshop (IEEE Cat. No.04EX940) Pub Date : 2004-11-10 DOI:10.1109/HLDVT.2004.1431257

V. Durairaj, P. Kalla

引用次数: 12

Abstract

This paper presents hypergraph partitioning based constraint decomposition procedures to guide Boolean satisfiability search. Variable-constraint relationships are modeled on a hypergraph and partitioning based techniques are employed to decompose the constraints. Subsequently, the decomposition is analyzed to solve the CNF-SAT problem efficiently. The contributions of this research are two-fold: 1) to engineer a constraint decomposition technique using hypergraph partitioning; 2) to engineer a constraint resolution method based on this decomposition. Preliminary experiments show that our approach is fast, scalable and can significantly increase the performance (often orders of magnitude) of the SAT engine.

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利用超图划分高效布尔可满足性

提出了基于超图划分的约束分解方法来指导布尔可满足性搜索。在超图上对变量约束关系进行建模，并采用基于划分的技术对约束进行分解。然后对分解进行分析，有效地解决了CNF-SAT问题。本研究的贡献有两个方面:1)设计了一种使用超图划分的约束分解技术;2)设计基于该分解的约束解析方法。初步实验表明，我们的方法是快速的，可扩展的，并且可以显着提高SAT引擎的性能(通常是数量级)。

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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Proceedings. Ninth IEEE International High-Level Design Validation and Test Workshop (IEEE Cat. No.04EX940)

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