HPC-gSpan: An FPGA-based parallel system for frequent subgraph mining

Abstract

Graph mining is an important research area within the domain of data mining. One of the most challenging tasks of graph mining is frequent subgraph mining. This work presents the first FPGA-based implementation, to the best of our knowledge, of the most efficient and well-known algorithm for the Frequent Subgraph Mining (FSM) problem, i.e. gSpan. The proposed system, named High Performance Computing-gSpan (HPC-gSpan), achieves manyfold speedup vs. the official software solution of the gboost library when executed on a high-end CPU for various real-world datasets.