Predictive Resource Scheduling
Predictive Resource Scheduling is a computational framework within resource forecasting that integrates predictive analytics to dynamically allocate and sequence resources by anticipating future demand, availability, and performance constraints through data-driven modeling.
111
Publications
5K
Citations
362
Authors
141
Institutions
Publications per year
2017–2026
58
Parents
111
Characterization and prediction of deep learning workloads in large-scale GPU datacenters
Qinghao Hu, Peng Sun, Shengen Yan et al. · 2021 · 120 citations · Full text
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141

Beihang University
Beijing, China
5 h-index
13 publications
333 citations
Tsinghua University
Beijing, China
3 h-index
6 publications
312 citations
Universitat Politècnica de Catalunya
Barcelona, Spain
3 h-index
9 publications
444 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
8 publications
439 citations

Barcelona Supercomputing Center
Barcelona, Spain
3 h-index
9 publications
444 citations

Southeast University
Nanjing, China
3 h-index
8 publications
190 citations
University of Illinois Urbana-Champaign
Urbana, United States
3 h-index
4 publications
221 citations
ShanghaiTech University
Shanghai, China
2 h-index
8 publications
100 citations
1–8 of 141
3 publications · 119 citations
3
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2 publications · 76 citations
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FGCS · 3 publications · 182 citations
3
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TON · 2 publications · 50 citations
2
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PVLDB · 2 publications · 35 citations
2
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