Distributed RankBoost Acceleration Using FPGA and MPI for Web Relevance Ranking

Web search engine ranks web pages according to their relevance to user queries, which is critical for the success of commercial search engines. Rank Boost algorithm is promising in Web relevance ranking area, while its computation complexity makes our existing implementations (including single node software-based implementation and a FPGA-based accelerator) too slow to reflect the dynamics of the Web. Moreover, previous implementations can not handle the huge web-scale data. As such, in this paper, we present the RankBoost implementation on a MPI-based distributed FPGA-based accelerators. Our results show that the combination of the coarse parallel efficiency of distributed system and the fine parallel efficiency of reconfigurable hardware accelerators can significantly increase the computing performance.