Chaff

TLDR

Boolean satisfiability is a widely studied combinatorial optimization problem, with extensive efforts to provide practical solutions for applications in electronic design automation and artificial intelligence, leading to several SAT packages such as GRASP and SATO that are widely used in research and industry; most complete solvers are variants of the Davis–Putnam search algorithm. The paper introduces Chaff, a new complete SAT solver designed to achieve significant performance gains. Chaff achieves these gains through careful engineering of the search, notably an efficient Boolean constraint propagation implementation and a low‑overhead decision strategy. Chaff achieves one to two orders of magnitude performance improvement on difficult SAT benchmarks compared to other solvers such as GRASP and SATO.

Abstract

Boolean Satisfiability is probably the most studied of combinatorial optimization/search problems. Significant effort has been devoted to trying to provide practical solutions to this problem for problem instances encountered in a range of applications in Electronic Design Automation (EDA), as well as in Artificial Intelligence (AI). This study has culminated in the development of several SAT packages, both proprietary and in the public domain (e.g. GRASP, SATO) which find significant use in both research and industry. Most existing complete solvers are variants of the Davis-Putnam (DP) search algorithm. In this paper we describe the development of a new complete solver, Chaff, which achieves significant performance gains through careful engineering of all aspects of the search - especially a particularly efficient implementation of Boolean constraint propagation (BCP) and a novel low overhead decision strategy. Chaff has been able to obtain one to two orders of magnitude performance improvement on difficult SAT benchmarks in comparison with other solvers (DP or otherwise), including GRASP and SATO.