Parallel Algorithm Mapping

Parallel Algorithm Mapping is a systematic process in parallel computing that assigns algorithmic tasks to specific processing units within a parallel architecture, differentiating itself from related scheduling and load-balancing techniques by focusing on the structural and temporal optimization of task-to-resource allocations to maximize concurrency and minimize communication overhead.

170

Publications

5.3K

Citations

466

Authors

189

Institutions

Publications per year

2017–2026

15

Authors

466

  1. YR
    Yves Robert

    École Normale Supérieure de Lyon, France

    5 publications · 110 citations

    5

    h-index

  2. MO
    Michael O’Boyle

    University of Edinburgh, United Kingdom

    3 publications · 301 citations

    3

    h-index

  3. SG
    Samik Gupta

    University of Oregon, United States

    3 publications · 94 citations

    3

    h-index

  4. JD
    Jack Dongarra

    University of Tennessee at Knoxville, United States

    3 publications · 64 citations

    3

    h-index

  5. BN
    Bhagirath Narahari

    George Washington University, United States

    3 publications · 64 citations

    3

    h-index

1–5 of 466

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 8 publications · 350 citations

    8

    h-index

  2. IEEE Transactions on Computers

    4 publications · 280 citations

    4

    h-index

  3. Journal of Parallel and Distributed Computing

    4 publications · 208 citations

    4

    h-index

  4. Computer

    3 publications · 194 citations

    3

    h-index

  5. Parallel Computing

    3 publications · 170 citations

    3

    h-index

1–5