利用切口宽度改进符号仿真和布尔可满足性

Dong Wang, E. Clarke, Yunshan Zhu, J. Kukula
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引用次数: 23

摘要

在本文中,我们提出了基于切线宽度的启发式算法来提高符号仿真和SAT算法的效率。这些算法是许多形式化验证技术的基础引擎。我们提出了一种新的计算变量排序的方法,以减少CNF/电路的切割宽度。结果表明,在符号仿真过程中,电路宽度和活bdd的峰值数是相等的。因此,在符号模拟过程中,使用减少门调度宽度的排序可以显著改善运行时和内存需求。研究表明,SAT问题的时间复杂度可以用公式宽度指数地限定,许多实际电路的公式宽度是公式长度的对数。我们开发了基于切线宽度的启发式算法,在实践中可以加快现有的SAT算法,特别是对于具有小切线宽度的SAT实例。我们在许多标准基准上展示了我们的方法的强大功能。
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Using cutwidth to improve symbolic simulation and Boolean satisfiability
In this paper, we propose cutwidth based heuristics to improve the efficiency of symbolic simulation and SAT algorithms. These algorithms are the underlying engines of many formal verification techniques. We present a new approach for computing variable orderings that reduce CNF/circuit cutwidth. We show that the circuit cutwidth and the peak number of live BDDs during symbolic simulation are equal. Thus using an ordering that reduces the cutwidth in scheduling the gates during symbolic simulation can significantly improve both the runtime and memory requirements. It has been shown that the time complexity of SAT problems can be bounded exponentially by the formula cutwidth and many practical circuits has cutwidth logarithmic of the size of the formulas. We have developed cutwidth based heuristics which in practice can speed up existing SAT algorithms, especially for SAT instances with small cutwidth. We demonstrate the power of our approach on a number of standard benchmarks.
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