Parallel Graph Search

Parallel Graph Search is a computational framework within parallel algorithms that systematically explores graph structures concurrently across multiple processing units to accelerate the discovery of paths, nodes, or solutions, distinguished from sequential graph search by its simultaneous execution of search operations on distributed or shared-memory architectures.

102

Publications

5.7K

Citations

292

Authors

147

Institutions

Publications per year

2017–2026

23

Authors

292

  1. TS
    Toyotaro Suzumura

    Tokyo Institute of Technology, Japan

    4 publications · 121 citations

    4

    h-index

  2. AB
    Aydın Buluç

    Lawrence Berkeley National Laboratory, United States

    3 publications · 94 citations

    3

    h-index

  3. KF
    Katsuki Fujisawa

    Tokyo Institute of Technology, Japan

    3 publications · 125 citations

    3

    h-index

  4. KU
    Koji Ueno

    Tokyo Institute of Technology, Japan

    3 publications · 78 citations

    3

    h-index

  5. AA
    Alok Aggarwal

    IBM (United States), United States

    3 publications · 155 citations

    3

    h-index

1–5 of 292

Venues

  1. SIAM Journal on Computing

    6 publications · 387 citations

    6

    h-index

  2. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 5 publications · 167 citations

    5

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 3 publications · 150 citations

    3

    h-index

  4. arXiv (Cornell University)

    Repository · 2 publications · 86 citations

    2

    h-index

  5. Communications of the ACM

    2 publications · 474 citations

    2

    h-index

1–5