A Circuit-Level Amoeba-Inspired SAT Solver
This work addresses hardware implementation challenges for SAT solvers, offering a more efficient approach for specific applications, though it appears incremental as it builds on AmbSAT with a focus on hardware compatibility.
The paper tackled the inefficiency of AmbSAT's parallelism on general-purpose hardware by proposing a circuit-level model (CL-AmbSAT) that uses simple combinational logic for variable updates, resulting in fewer iterations than ProbSAT and AmbSAT in simulations on randomly generated SAT instances.
AmbSAT (or AmoebaSAT) is a biologically-inspired stochastic local search (SLS) solver to explore solutions to the Boolean satisfiability problem (SAT). AmbSAT updates multiple variables in parallel at every iteration step, and thus AmbSAT can find solutions with a fewer number of iteration steps than some other conventional SLS solvers for a specific set of SAT instances. However, the parallelism of AmbSAT is not compatible with general-purpose microprocessors in that many clock cycles are required to execute each iteration; thus, AmbSAT requires special hardware that can exploit the parallelism of AmbSAT to quickly find solutions. In this paper, we propose a circuit model (hardware-friendly algorithm) that explores solutions to SAT in a similar way to AmbSAT, which we call circuit-level AmbSAT (CL-AmbSAT). We conducted numerical simulation to evaluate the search performance of CL-AmbSAT for a set of randomly generated SAT instances that was designed to estimate the scalability of our approach. Simulation results showed that CL-AmbSAT finds solutions with a fewer iteration number than a powerful SLS solver, ProbSAT, and outperforms even AmbSAT. Since CL-AmbSAT uses simple combinational logic to update variables, CL-AmbSAT can be easily implemented in various hardware.