Workload Partitioning

Workload Partitioning is a computational task distribution strategy that belongs to the class of system optimization methods, specifically distinguished by its allocation of subtasks across heterogeneous processing units in distributed architectures to enhance energy efficiency, accelerate execution, and maximize throughput in mobile and accelerator-based computing environments.

322

Publications

15.1K

Citations

941

Authors

355

Institutions

Publications per year

2017–2026

87

Authors

941

  1. ÜV
    Ümit V. Çatalyürek

    The Ohio State University, United States

    5 publications · 289 citations

    5

    h-index

  2. BV
    Bharadwaj Veeravalli

    National University of Singapore, Singapore

    5 publications · 165 citations

    5

    h-index

  3. SB
    Sanjoy Baruah

    University of North Carolina at Chapel Hill, United States

    4 publications · 161 citations

    4

    h-index

  4. JN
    Jianwei Niu

    Beihang University, China

    4 publications · 121 citations

    4

    h-index

  5. AB
    Andrew B. Kahng

    University of California San Diego, United States

    4 publications · 499 citations

    4

    h-index

1–5 of 941

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 17 publications · 804 citations

    17

    h-index

  2. IEEE Transactions on Computers

    13 publications · 1.3K citations

    13

    h-index

  3. Journal of Parallel and Distributed Computing

    6 publications · 208 citations

    6

    h-index

  4. The Journal of Supercomputing

    5 publications · 125 citations

    5

    h-index

  5. Journal of Network and Computer Applications

    JNCA · 3 publications · 237 citations

    3

    h-index

1–5