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GPU-based Graph Traversal on Compressed Graphs

Summary: GPU-based graph traversal on compressed graphs enables processing graphs larger than device memory. Introduces Two-Phase Traversal and Task-Stealing to mitigate SIMT divergence and workload imbalance, plus Warp-centric Decoding and Residual Segmentation for power-law graphs, achieving 2x–18x compression with competitive efficiency. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5745
Venue
SIGMOD
Year
2019
Pagerank
6.8629037e-05
Overall Rank
4,157 | 71.49%
DOI
10.1145/3299869.3319871

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{sha_sigmod19,
        title = {{GPU-based Graph Traversal on Compressed Graphs}},
        author = {Sha, Mo and Li, Yuchen and Tan, Kian-Lee},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3319871},
        url = {https://dl.acm.org/doi/10.1145/3299869.3319871},
        year = {2019}
}

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