Parallel Searching Algorithms

Parallel Searching Algorithms is a computational methodology within parallel computation that fundamentally consists of simultaneous exploration strategies to locate specific elements or patterns in a data structure by distributing the search task across multiple processing units, thereby differentiating it from sequential search techniques through concurrent execution.

221

Publications

13.6K

Citations

523

Authors

265

Institutions

Publications per year

2017–2026

21

Authors

523

  1. VK
    Vipin Kumar

    The University of Texas at Austin, United States

    6 publications · 361 citations

    6

    h-index

  2. VN
    V. Nageshwara Rao

    The University of Texas at Austin, United States

    4 publications · 198 citations

    4

    h-index

  3. PC
    Philippe Codognet

    Sorbonne Université, France

    4 publications · 78 citations

    4

    h-index

  4. RE
    Richard E. Korf

    University of California, Los Angeles, United States

    4 publications · 207 citations

    4

    h-index

  5. AK
    Akihiro Kishimoto

    University of Alberta, Canada

    4 publications · 132 citations

    4

    h-index

1–5 of 523

Venues

  1. Journal of Parallel and Distributed Computing

    5 publications · 147 citations

    5

    h-index

  2. Artificial Intelligence

    4 publications · 178 citations

    4

    h-index

  3. 4

    h-index

  4. Physical Review Letters

    PRL · 3 publications · 141 citations

    3

    h-index

  5. ICGA Journal

    3 publications · 90 citations

    3

    h-index

1–5