Distributed Memory Algorithms

Distributed Memory Algorithms is a class of parallel numerical linear algebra algorithms designed for scalable algorithm design, in which computations are performed on data distributed across multiple processing units with non-uniform memory access, each processor accessing its own local memory exclusively and communicating with others explicitly through message passing to coordinate operations.

296

Publications

15.2K

Citations

651

Authors

260

Institutions

Publications per year

2017–2026

25

Authors

651

  1. JD
    James Demmel

    University of California, Berkeley, United States

    9 publications · 436 citations

    9

    h-index

  2. JC
    Jaeyoung Choi

    Soongsil University, South Korea

    8 publications · 818 citations

    8

    h-index

  3. JD
    Jack Dongarra

    University of Tennessee at Knoxville, United States

    8 publications · 832 citations

    8

    h-index

  4. PS
    P. Sadayappan

    The Ohio State University, United States

    7 publications · 357 citations

    7

    h-index

  5. DW
    David Walker

    Cardiff University, United Kingdom

    6 publications · 759 citations

    6

    h-index

1–5 of 651

Venues

  1. Parallel Computing

    16 publications · 457 citations

    13

    h-index

  2. SIAM Journal on Scientific Computing

    9 publications · 1K citations

    9

    h-index

  3. Journal of Parallel and Distributed Computing

    9 publications · 438 citations

    9

    h-index

  4. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 6 publications · 184 citations

    6

    h-index

  5. Computer Physics Communications

    5 publications · 504 citations

    5

    h-index

1–5