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A Semi-Tensor Product Based All Solutions Boolean Satisfiability Solver

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Abstract

Boolean satisfiability (SAT) is widely used as a solver engine in electronic design automation (EDA). Typically, SAT is used to determine whether one or more groups of variables can be combined to form a true formula. All solutions SAT (AllSAT) is a variant of the SAT problem. In the fields of formal verification and pattern generation, AllSAT is particularly useful because it efficiently enumerates all possible solutions. In this paper, a semi-tensor product (STP) based AllSAT solver is proposed. The solver can solve instances described in both the conjunctive normal form (CNF) and circuit form. The implementation of our method differs from incremental enumeration because we do not add blocking conditions for existing solutions, but rather compute the matrices to obtain all the solutions in one pass. Additionally, the logical matrices support a variety of logic operations. Results from experiments with MCNC benchmarks using CNF-based and circuit-based forms show that our method can accelerate CPU time by 8.1x (238x maximum) and 19.9x (72x maximum), respectively.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China

    Hong-Yang Pan & Zhu-Fei Chu

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  1. Hong-Yang Pan
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  2. Zhu-Fei Chu
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Correspondence to Zhu-Fei Chu.

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Pan, HY., Chu, ZF. A Semi-Tensor Product Based All Solutions Boolean Satisfiability Solver. J. Comput. Sci. Technol. 38, 702–713 (2023). https://doi.org/10.1007/s11390-022-1981-4

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