Augmenting ML-based Predictive Modelling with NLP to Forecast a Job's Power Consumption

Author:

Antici Francesco1ORCID,Yamamoto Keiji2ORCID,Domke Jens2ORCID,Kiziltan Zeynep1ORCID

Affiliation:

1. Department of Computer Science and Engineering, University of Bologna, Italy

2. RIKEN Center for Computational Science (R-CCS), Japan

Publisher

ACM

Reference17 articles.

1. Francesco Antici , Andrea Borghesi , and Zeynep Kiziltan . 2023. Online Job Failure Prediction in an HPC System . In Euro-Par 2023: Parallel Processing Workshops: Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28–September 1 , 2023 , Revised Selected Papers. Springer Nature . Francesco Antici, Andrea Borghesi, and Zeynep Kiziltan. 2023. Online Job Failure Prediction in an HPC System. In Euro-Par 2023: Parallel Processing Workshops: Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28–September 1, 2023, Revised Selected Papers. Springer Nature.

2. Simple Power-Aware Scheduler to Limit Power Consumption by HPC System within a Budget

3. Predictive Modeling for Job Power Consumption in HPC Systems

4. Scheduling-based power capping in high performance computing systems

5. Power Capping in High Performance Computing Systems

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