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Using cutwidth to improve symbolic simulation and Boolean satisfiability

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4 Author(s)
Wang, D. ; Carnegie Mellon Univ., Pittsburgh, PA, USA ; Clarke, E. ; Yunshan Zhu ; Kukula, J.

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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High-Level Design Validation and Test Workshop, 2001. Proceedings. Sixth IEEE International

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