Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
A bitstream reconfigurable FPGA implementation of the WSAT algorithm
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on low power electronics and design
Local Search Algorithms for SAT: An Empirical Evaluation
Journal of Automated Reasoning
Reconfigurable Hardware SAT Solvers: A Survey of Systems
IEEE Transactions on Computers
Old resolution meets modern SLS
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Evidence for invariants in local search
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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WSAT and its variants are one of the best performing stochastic local search algorithms for the satisfiability (SAT) problem. In this article, we propose an approach for solving large 3-SAT problems on FPGA using a WSAT algorithm. In hardware solvers, it is important to solve large problems efficiently. In WSAT algorithms, an assignment of binary values to the variables that satisfy all clauses is searched by repeatedly choosing a variable in an unsatisfied clause using a heuristic, and flipping its value. In our solver, (1) only the clauses that may be unsatisfied by the flipping are evaluated in parallel to minimize the circuit size, and (2) several independent tries are executed at the same time on the pipelined circuit to achieve high performance. Our FPGA solver can solve larger problems than previous works with less hardware resources, and shows higher performance.