Concepedia

Parallel Maximum Finding

Parallel Maximum Finding is a parallel algorithmic method belonging to the class of search algorithms, distinguished by its purpose of identifying the maximum element in a data set through concurrent processing to reduce time complexity relative to sequential approaches.

2

Publications

365

Citations

3

Authors

4

Institutions

Publications per year

2017–2026

0

Parents

Publications

2

1–2 of 2

Authors

3

  1. YS
    Yossi Shiloach

    IBM Research - Haifa, Israel

    1 publications · 239 citations

    1

    h-index

  2. BO
    Bokhari

    University of Engineering and Technology Lahore, Pakistan

    1 publications · 126 citations

    1

    h-index

  3. UV
    Uzi Vishkin

    University of Maryland, College Park, United States

    1 publications · 239 citations

    1

    h-index

1–3 of 3

Institutions

4

  1. University of Engineering and Technology Lahore

    Lahore, Pakistan

    1 h-index

    1 publications

    126 citations

  2. Technion – Israel Institute of Technology

    Haifa, Israel

    1 h-index

    1 publications

    239 citations

  3. Langley Research Center

    Hampton, United States

    1 h-index

    1 publications

    126 citations

  4. IBM Research - Haifa

    Haifa, Israel

    1 h-index

    1 publications

    239 citations

1–4 of 4

Venues

  1. Journal of Algorithms

    1 publications · 239 citations

    1

    h-index

  2. IEEE Transactions on Computers

    1 publications · 126 citations

    1

    h-index

1–2