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Application Driven Graph Partitioning

Summary: Application-driven hybrid partitioning learns a cost model for A via poly regression to refine edge-cut/vertex-cut into a hybrid partition. Identifies a condition for partition transparency; yields up to 22.5x speedups on real/synthetic graphs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6022
Venue
SIGMOD
Year
2020
Pagerank
6.740899e-05
Overall Rank
4,365 | 70.06%
DOI
10.1145/3318464.3389745

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{fan_sigmod20,
        title = {{Application Driven Graph Partitioning}},
        author = {Fan, Wenfei and Jin, Ruochun and Liu, Muyang and Lu, Ping and Luo, Xiaojian and Xu, Ruiqi and Yin, Qiang and Yu, Wenyuan and Zhou, Jingren},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3389745},
        url = {https://dl.acm.org/doi/10.1145/3318464.3389745},
        year = {2020}
}

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