Predicting running time of aerodynamic jobs in HPC system by combining supervised and unsupervised learning method

Predicting running time of aerodynamic jobs in HPC system by combining supervised and unsupervised learning method

Abstract Improving resource utilization is an important goal of high-performance computing systems of supercomputing centers. To meet this goal, the job scheduler of high-performance computing systems often uses backfilling scheduling to fill short-time jobs into job gaps at the front of the queue....

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Bibliographic Details
Main Authors: Hao Wang, Yi-Qin Dai, Jie Yu, Yong Dong
Format: Article
Language:English
Published: SpringerOpen 2021-08-01
Series:Advances in Aerodynamics
Subjects:
High-performance computing
Job scheduling
Job running time prediction
Machine learning
Prediction accuracy
Underestimation rate
Online Access:https://doi.org/10.1186/s42774-021-00077-8

Internet

https://doi.org/10.1186/s42774-021-00077-8

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