EHSAT: An Efficient RTL Satisfiability Solver Using an Extended DPLL Procedure

This paper presents an efficient algorithm to solve the satisfiability (SAT) problem for RTL designs using a complete hybrid branch-and-bound strategy with conflict-driven learning. The main framework is the extended Davis-Putnam-Logemann-Loveland procedure (DPLL) which is a unified procedure combining Boolean logic and arithmetic operations. A hybrid two- literal-watching scheme and interval reasoning based on RTL predicates are used as the powerful hybrid constraint propagation strategies. Conflict-based learning is also implemented as another important technique to enhance efficiency. Comparisons with a state-of-the-art RTL SAT solver, a SMT solver and an ILP solver show that EHSAT outperforms these solvers for RTL satisfiability problems.