Scalable Algorithm Design

Scalable Algorithm Design is a methodology within parallel and distributed algorithmics that constructs algorithms whose performance and resource efficiency provably remain acceptable or improve as input size and available processing resources increase, by systematically exploiting concurrency, locality, and low-overhead coordination.

1.6K

Publications

98.2K

Citations

4.5K

Authors

988

Institutions

Publications per year

2017–2026

459

Authors

4.5K

  1. DA
    David A. Bader

    Georgia Institute of Technology, United States

    13 publications · 894 citations

    13

    h-index

  2. PD
    Pradeep Dubey

    Intel (United States), United States

    11 publications · 950 citations

    11

    h-index

  3. NS
    Nir Shavit

    Tel Aviv University, Israel

    11 publications · 1K citations

    11

    h-index

  4. JD
    Jack Dongarra

    University of Tennessee at Knoxville, United States

    11 publications · 853 citations

    11

    h-index

  5. AB
    Aydın Buluç

    Lawrence Berkeley National Laboratory, United States

    12 publications · 725 citations

    11

    h-index

1–5 of 4.5K

Venues

  1. arXiv (Cornell University)

    Repository · 95 publications · 5.1K citations

    34

    h-index

  2. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 55 publications · 2.3K citations

    28

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 33 publications · 2K citations

    24

    h-index

  4. SIAM Journal on Scientific Computing

    22 publications · 1.7K citations

    18

    h-index

  5. IEEE Transactions on Computers

    18 publications · 1.1K citations

    17

    h-index

1–5