NVIDA CUDA Architecture-Based Parallel SAT Solver

The SAT problem is the first NP-complete problem. So far there is no algorithm that can solve it in polynomial time. Over the past decade, the development of efficient and scalable algorithms has dramatically leveraged the ability of solving SAT problem instances involving tens of thousands of variables and millions of constraints. But as industry demand is increasing, a faster SAT solver is needed, so people begin to exploit parallel computing power. Recently, GPU has shown an appealing potential of parallel computing capability and its versatility allows it to be used for non-graphic algorithms. In addition, GPU manufacturers are actively improving the architecture of graphics cards to make them adapt to the general purpose parallel computation, to complete them with on-board shared memory and the general-purpose APIs for parallel programming. There is reason to believe that in the near future, GPU architecture might be able to be applied to problems where traditional multi-processors parallel architecture is being used. So, applying new GPU architecture to the SAT solver might bring a breakthrough in performance.