FPGA-based SAT solvers have the potential to dramatically accelerate SAT solving by effectively exploiting finegrained pipeline parallelism in a manner which is not achievable with regular processors. Previous hardware-based approaches have relied on on-chip memory resources to store data which, similar to a CPU cache, are very fast, but are also very limited in size. For hardware-based SAT approaches to scale to real-world instances, it is necessary to utilise large amounts of off-chip memory. We present novel techniques for storing and retrieving SAT clauses using a custom multi-port memory interface to off-chip DRAM which is connected to a processor core implemented on a medium sized FPGA on the BEE3 system. Since DRAM is slower than on-chip memory resources, the parallelisation which can be achieved is limited by memory throughput. We present the design and implementation of a new parallel architecture that tackles this problem and estimate the performance of our approach with memory benchmarks.
['Leopold Haller', 'Satnam Singh']
Relieving capacity limits on FPGA-based SAT-solvers