SC22 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Technical Papers Archive

VSGM: View-Based GPU-Accelerated Subgraph Matching on Large Graphs


Authors: Guanxian Jiang, Qihui Zhou, Tatiana Jin, Boyang Li, Yunjian Zhao, Yichao Li, and James Cheng (Chinese University of Hong Kong (CUHK))

Abstract: Subgraph matching is a fundamental building block in graph analytics. Due to its high time complexity, GPU-based solutions have been proposed for subgraph matching. Most existing GPU-based works can only cope with relatively small graphs that fit in GPU memory. To support efficient subgraph matching on large graphs, we propose a view-based method to hide communication overhead and improve GPU utilization. We develop VSGM, a subgraph matching framework that supports efficient pipelined execution and multi-GPU architecture. Extensive experimental evaluation shows that VSGM significantly outperforms the state-of-the-art solutions.




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