An FPGA-based Stochastic SAT Solver Leveraging Inter-Variable Dependencies

Control rules of Internet of Things (IoT) and embedded systems are often representable in Satisfiability (SAT) problem. This paper proposes a solution search acceleration technique applicable to hardware SAT solvers by leveraging inter-variable dependencies inherited in SAT-encoded realistic applications. We applied our technique on the FPGA implementation of AmoebaSAT, a state-of-the-art stochastic SAT algorithm. Our evaluation on SAT instances from two different IoT-oriented domains demonstrated a significant speedup in solution search against a state-of-the-art hardware SAT solver while incurring almost no effect on hardware implementation compared with the original (dependency-unaware) implementation.