19941

Fast Gunrock Subgraph Matching (GSM) on GPUs

Leyuan Wang, John D. Owens
University of California, Davis CA 95616, USA
arXiv:2003.01527 [cs.DC], (1 Mar 2020)

@misc{wang2020fast,

   title={Fast Gunrock Subgraph Matching (GSM) on GPUs},

   author={Leyuan Wang and John D. Owens},

   year={2020},

   eprint={2003.01527},

   archivePrefix={arXiv},

   primaryClass={cs.DC}

}

In this paper, we propose a novel method, GSM (Gunrock Subgraph Matching), to compute graph matching (subgraph isomorphism) on GPUs. In contrast to previous approaches, GSM is BFS-based: possible matches are explored simultaneously in a breadth-first strategy and thus can be mapped onto GPUs in a massively parallel fashion. Our implementation on the Gunrock graph analytics framework follows a filtering-and-verification strategy. While previous work requires one-/two-step joining, we use one-step verification to decide the candidates in current frontier of nodes. Our implementation has a speedup up to 4x over previous GPU state-of-the-art implementation.

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