Performance-aware Placement

Performance-Aware Placement is a workload placement strategy that belongs to the class of performance-optimized resource allocation methods, distinguished by its explicit incorporation of system and application performance metrics to guide placement decisions in computing environments.

43

Publications

2K

Citations

156

Authors

74

Institutions

Publications per year

2017–2026

12

Authors

156

  1. LQ
    Lili Qiu

    The University of Texas at Austin, United States

    2 publications · 70 citations

    2

    h-index

  2. HP
    Himabindu Pucha

    Purdue University West Lafayette, United States

    2 publications · 70 citations

    2

    h-index

  3. JJ
    Jinhwan Jeon

    Seoul National University, South Korea

    2 publications · 62 citations

    2

    h-index

  4. JB
    Jun Bi

    Tsinghua University, China

    2 publications · 45 citations

    2

    h-index

  5. SL
    Sunghyun Lee

    Seoul National University, South Korea

    2 publications · 62 citations

    2

    h-index

1–5 of 156

Venues

  1. 2

    h-index

  2. CiteSeer X (The Pennsylvania State University)

    Repository · 1 publications · 155 citations

    1

    h-index

  3. 1

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  4. The Journal of Supercomputing

    1 publications · 11 citations

    1

    h-index

  5. International Conference on Machine Learning

    Conference · 1 publications · 57 citations

    1

    h-index

1–5