Accelerating Triangle-Connected Truss Community Search Across Heterogeneous Hardware
Summary: Tensor-based acceleration of triangle-connected k-truss community search (k-TTC) on heterogeneous hardware. Recasts EquiTree-style index construction/search/maintenance as batched supernode/superedge operations over triangle types, yielding ~100x speedups on GPUs and dynamic graph support. (summarized by gpt-5-mini on Apr 11 2026)
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Authors
- 1. Junchao Ma (Wuhan University)
- 2. Xin Yan (Wuhan University)
- 3. Yuanyuan Zhu (Wuhan University)
- 4. Guojing Li (Wuhan University)
- 5. Hao Zhang (Chinese University of Hong Kong)
- 6. Jeffrey Xu Yu (Hong Kong University of Science and Technology)
BibTeX Citation
@inproceedings{ma_sigmod26,
title = {{Accelerating Triangle-Connected Truss Community Search Across Heterogeneous Hardware}},
author = {Ma, Junchao and Yan, Xin and Zhu, Yuanyuan and Li, Guojing and Zhang, Hao and Yu, Jeffrey Xu},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786620},
url = {https://dl.acm.org/doi/10.1145/3786620},
year = {2026}
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