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GRAPE: Parallelizing Sequential Graph Computations

Summary: GRAPE parallelizes sequential graph algorithms via a simultaneous fixed-point model, enabling partial/incremental evaluation across the graph. Unlike prior systems, it requires no algorithm rewrites; under monotonicity it terminates with correct results for plugged-in sequential algorithms; demonstrates performance vs state-of-the-art and a social-media marketing use case. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11666
Venue
VLDB
Year
2017
Pagerank
5.9890886e-05
Overall Rank
6,066 | 58.39%
DOI
10.14778/3137765.3137772

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{fan_vldb17,
        title = {{GRAPE: Parallelizing Sequential Graph Computations}},
        author = {Fan, Wenfei and Xu, Jingbo and Wu, Yinghui and Yu, Wenyuan and Jiang, Jiaxin},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {12},
        pages = {1889--1902},
        doi = {10.14778/3137765.3137772},
        url = {https://doi.org/10.14778/3137765.3137772},
        year = {2017}
}

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