A SAT-based algorithm for reparameterization in symbolic simulation

P. Chauhan, E. Clarke, D. Kroening
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引用次数: 25

Abstract

Parametric representations used for symbolic simulation of circuits usually use BDDs. After a few steps of symbolic simulation, state set representation is converted from one parametric representation to another smaller representation, in a process called reparameterization. For large circuits, the reparametrization step often results in a blowup of BDDs and is expensive due to a large number of quantifications of input variables involved. Efficient SAT solvers have been applied successfully for many verification problems. This paper presents a novel SAT-based reparameterization algorithm that is largely immune to the large number of input variables that need to be quantified. We show experimental results on large industrial circuits and compare our new algorithm to both SAT-based Bounded Model Checking and BDD based symbolic simulation. We were able to achieve on average 3x improvement in time and space over BMC and able to complete many examples that BDD based approach could not even finish.
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符号仿真中基于sat的重参数化算法
用于电路符号仿真的参数表示通常使用bdd。经过几个步骤的符号模拟后,状态集表示从一种参数表示转换为另一种较小的表示,这个过程称为重新参数化。对于大型电路,重参数化步骤通常会导致bdd的爆炸,并且由于涉及大量输入变量的量化,成本很高。高效的SAT求解器已成功地应用于许多验证问题。本文提出了一种新的基于sat的再参数化算法,该算法在很大程度上不受需要量化的大量输入变量的影响。我们展示了在大型工业电路上的实验结果,并将我们的新算法与基于sat的有界模型检查和基于BDD的符号仿真进行了比较。我们能够在时间和空间上实现比BMC平均3倍的改进,并且能够完成许多基于BDD的方法甚至无法完成的示例。
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