gMatch: Fine-Grained and Hardware-Efficient Subgraph Matching on GPUs
Summary: gMatch enables GPU subgraph matching with fine-grained execution, warp-level batch exploration, and lightweight load balancing, reducing memory overhead and thread underutilization. It outscales prior matchers and small-pattern miners on large queries and datasets. (summarized by gpt-5.6-luna on Jul 09 2026)
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Authors
- 1. Weitian Chen (Shanghai Jiao Tong University)
- 2. Shixuan Sun (Shanghai Jiao Tong University)
- 3. Cheng Chen (ByteDance)
- 4. Yongmin Hu (ByteDance)
- 5. Yingqian Hu (ByteDance)
- 6. Minyi Guo (Guizhou University)
BibTeX Citation
@article{chen_vldb26,
title = {{gMatch: Fine-Grained and Hardware-Efficient Subgraph Matching on GPUs}},
author = {Chen, Weitian and Sun, Shixuan and Chen, Cheng and Hu, Yongmin and Hu, Yingqian and Guo, Minyi},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {8},
pages = {1740--1753},
doi = {10.14778/3811243.3811248},
url = {https://doi.org/10.14778/3811243.3811248},
year = {2026}
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