Graph Processing

Graph Processing is a computational paradigm that specializes in the efficient manipulation and analysis of graph-structured data through vertex-edge representations, distinguishing itself from other GPU computing methods by its focus on irregular, sparse, and highly connected data traversals.

2K

Publications

132.4K

Citations

5.3K

Authors

1.2K

Institutions

Publications per year

2017–2026

1.1K

Authors

5.3K

  1. HJ
    Hai Jin

    Huazhong University of Science and Technology, China

    36 publications · 1.1K citations

    22

    h-index

  2. BH
    Bingsheng He

    National University of Singapore, Singapore

    34 publications · 1.5K citations

    22

    h-index

  3. XL
    Xiaofei Liao

    Huazhong University of Science and Technology, China

    20 publications · 566 citations

    16

    h-index

  4. MB
    Maciej Besta

    ETH Zurich, Switzerland

    19 publications · 820 citations

    15

    h-index

  5. XL
    Xuemin Lin

    UNSW Sydney, Australia

    16 publications · 833 citations

    15

    h-index

1–5 of 5.3K

Venues

  1. arXiv (Cornell University)

    Repository · 133 publications · 9.5K citations

    43

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 58 publications · 4.3K citations

    32

    h-index

  3. IEEE Transactions on Signal Processing

    28 publications · 2.5K citations

    25

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 36 publications · 1.6K citations

    22

    h-index

  5. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 29 publications · 1.3K citations

    22

    h-index

1–5