Parallel Data Structures

Parallel Data Structures is a class of data organization schemes designed to enable concurrent access and modification by multiple processing elements, distinguished by their explicit support for parallelism through synchronization mechanisms and memory access patterns that ensure correctness and efficiency in shared or distributed memory systems.

1.9K

Publications

101.6K

Citations

4.2K

Authors

1K

Institutions

Publications per year

2017–2026

234

Authors

4.2K

  1. GE
    Guy E. Blelloch

    Carnegie Mellon University, United States

    31 publications · 2.1K citations

    24

    h-index

  2. KP
    Keshav Pingali

    The University of Texas at Austin, United States

    15 publications · 1.9K citations

    15

    h-index

  3. JS
    Julian Shun

    Carnegie Mellon University, United States

    16 publications · 668 citations

    15

    h-index

  4. NS
    Nir Shavit

    Tel Aviv University, Israel

    15 publications · 1.3K citations

    14

    h-index

  5. UV
    Uzi Vishkin

    University of Maryland, College Park, United States

    13 publications · 1.5K citations

    12

    h-index

1–5 of 4.2K

Venues

  1. Journal of Parallel and Distributed Computing

    57 publications · 2.9K citations

    28

    h-index

  2. Parallel Computing

    62 publications · 2.8K citations

    28

    h-index

  3. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 38 publications · 1.5K citations

    23

    h-index

  4. IEEE Transactions on Computers

    47 publications · 3.7K citations

    23

    h-index

  5. ACM SIGPLAN Notices

    29 publications · 970 citations

    18

    h-index

1–5