Heterogeneity-aware Scheduling

Heterogeneity-Aware Scheduling is a task scheduling methodology that explicitly accounts for the diverse computational capabilities, resource configurations, and performance characteristics of heterogeneous processing units to optimize workload distribution and execution efficiency.

211

Publications

12K

Citations

642

Authors

300

Institutions

Publications per year

2017–2026

68

Authors

642

  1. HJ
    Howard Jay Siegel

    Colorado State University, United States

    9 publications · 1.2K citations

    9

    h-index

  2. DG
    Douglas G. Down

    McMaster University, Canada

    6 publications · 151 citations

    6

    h-index

  3. GX
    Guoqi Xie

    Hunan University, China

    4 publications · 241 citations

    4

    h-index

  4. AA
    Anthony A. Maciejewski

    Colorado State University, United States

    4 publications · 549 citations

    4

    h-index

  5. RL
    Renfa Li

    Hunan University, China

    4 publications · 241 citations

    4

    h-index

1–5 of 642

Venues

  1. Journal of Parallel and Distributed Computing

    13 publications · 970 citations

    13

    h-index

  2. The Journal of Supercomputing

    10 publications · 469 citations

    10

    h-index

  3. Future Generation Computer Systems

    FGCS · 9 publications · 487 citations

    9

    h-index

  4. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 9 publications · 612 citations

    9

    h-index

  5. Parallel Computing

    5 publications · 377 citations

    5

    h-index

1–5