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Cache-Efficient Fork-Processing Patterns on Large Graphs

Summary: FPP on large graphs suffers cache misses on multi-core systems. ForkGraph partitions graphs into LLC-sized blocks, buffers FPP queries per partition, and uses cache-resident sequential processing with intra- and inter-partition scheduling (yielding and priority-based), achieving work-efficiency and large speedups over Ligra, Gemini, GraphIt. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6206
Venue
SIGMOD
Year
2021
Pagerank
6.1501992e-05
Overall Rank
5,612 | 61.50%
DOI
10.1145/3448016.3457253

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{lu_sigmod21,
        title = {{Cache-Efficient Fork-Processing Patterns on Large Graphs}},
        author = {Lu, Shengliang and Sun, Shixuan and Paul, Johns and Li, Yuchen and He, Bingsheng},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3457253},
        url = {https://dl.acm.org/doi/10.1145/3448016.3457253},
        year = {2021}
}

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