Boosting the Performance of CDCL-Based SAT Solvers by Exploiting Backbones and Backdoors
布尔结构措施
本研究考虑的措施包括与主干和后门相关的措施: 主干大小、主干频率和后门大小。
当前SAT主要关键技术及其相关文献——参见下面这段叙述。 The annual SAT competitions have become an essential event for the distribution of SAT benchmarks and the development of new SAT-solving methods [5]. Sequential SAT solvers compete mainly in three categories: industrial, crafted, and random tracks. The SAT competitions have demonstrated how difficult it is for SAT solvers to perform well across all categories. Results show that conflict-driven clause-learning (CDCL) SAT solvers were most performant for solving industrial and crafted SAT benchmarks, whereas look-ahead and Stochastic Local Search (SLS)-based SAT solvers have dominated the random category [5]. Modern implementations of CDCL SAT solvers employ a lot of heuristics. Some of them can be considered baseline, such as the Variable State Independent Decaying Sum (VSIDS) [6], restarts [7], and Literal Block Distance (LBD) [8]. Several others were incorporated recently, including: Learnt Clause Minimization (LCM) [9], Distance (Dist) heuristic [10], Chronological Backtracking (ChronoBT) [11], duplicate learnts heuristic [12], Conflict History-Based (CHB) heuristic [13], Learning Rate-based Branching (LRB) heuristic [14], and the SLS component [15].
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The results of the SAT competitions have led researchers to conclude that (1) industrial, crafted, and random SAT instances have distinct structures, and (2) SAT-solving methods could exploit such structures. |
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我们对主干和后门提出了三种新的相关措施:主干频率、主干覆盖率和后门覆盖率(读者可参阅附录A,其中从2002-2020年SAT竞赛中提取的工业、手工和随机基准实例的主干和后门相关措施的证据进行了调查。 | |