Toward Building a Digital Twin of Job Scheduling and Power Management on an HPC System

Ohmura, Tatsuyoshi; Shimomura, Yoichi; Egawa, Ryusuke; Takizawa, Hiroyuki

doi:10.1007/978-3-031-22698-4_3

Cited by 5 publications

(2 citation statements)

References 22 publications

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“…All versions allow to test different Slurm parameters without altering the corresponding production system. Slurm can be combined with other schedulers like NQSV and digital twins [5]. However, since every setup is different, a custom solution is necessary.…”

Section: Scheduling Simulation Frameworkmentioning

confidence: 99%

“…Currently, the influence of different internal and external factors on the energy efficiency of the HPC cluster at PTB are not well understood. A digital twin can help in understanding those factors in detail and test changes to the system configuration without adverse effects to the production system and is commonly used for this purpose [5]. However, optimization goals and systems differ from every site and cluster.…”

Section: Introductionmentioning

confidence: 99%

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Towards an HPC cluster digital twin and scheduling framework for improved energy efficiency

Kammeyer,

Burger,

Lübbert

et al. 2023

Annals of Computer Science and Information Systems

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Demand for compute resources and thus energy demand for HPC is steadily increasing while the energy market transforms to renewable energy and is facing significant price increases. Optimizing energy efficiency of HPC clusters is therefore a major concern. Different possible optimization dimensions are discussed in this paper. This paper presents a digital twin design for analyzing and reducing energy consumption of a real-world HPC system. The digital twin is based on the HPC cluster at PTB. The digital twin receives information from multiple internal and external data sources to cover the different optimization opportunities. The digital twin also consists of a scheduling simulation framework that uses the data from the digital twin and real-world job traces to test the influence of the different parameters on the HPC cluster.

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Section: Scheduling Simulation Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%