Fast Gunrock Subgraph Matching (GSM) on GPUs
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.
March 8, 2020 by hgpu
