IRSMG: Accelerating Inexact RDF Subgraph Matching on the GPU

Many approaches have been proposed to solve subgraph matching problem based on filter-and-refine strategy. The efficiency of those existing serial approaches relies on the computational capabilities of CPU. In this paper, we propose an RDF subgraph matching algorithm based on type-isomorphism using GPU since GPU has higher computational performance, more scalability, and lower price than CPU. Firstly, we present a concurrent matching model for type-isomorphism so that subgraph matching can be tackled in a parallel way. Secondly, we develop a parallel algorithm for capturing our proposed concurrent matching model and implement a prototype called IRSMG using GPU. Finally, we evaluate IRSMG on the benchmark datasets LUBM. The experiments show that IRSMG significantly outperforms the state-of-the-art algorithms on the CPU.