Prediction and characterization of application power use in a high‐performance computing environment

Statistical Analysis and Data Mining

Bugbee, Bruce¹  Gruchalla, Kenny¹  Phillips, Caleb¹  Purkayastha, Avi¹  Egan, Hilary²  Elmore, Ryan³ 

[1] National Renewable Energy Laboratory Computational Sciences Center Golden Colorado;University of Colorado Department of Astrophysical and Planetary Sciences Boulder Colorado;University of Denver Department of Business Information and Analytics Denver Colorado

关键词: HPC;    queueing systems;    renewable energy;    scientific computing;   

DOI  :  10.1002/sam.11339

学科分类：社会科学、人文和艺术（综合）

来源: John Wiley & Sons, Inc.

【 摘 要 】

Power use in data centers and high-performance computing (HPC) facilities has grown in tandem with increases in the size and number of these facilities. Substantial innovation is needed to enable meaningful reduction in energy footprints in leadership-class HPC systems. In this paper, we focus on characterizing and investigating application-level power usage. We demonstrate potential methods for predicting power usage based on a priori and in situ characteristics. Finally, we highlight a potential use case of this method through a simulated power-aware scheduler using historical jobs from a real scientific HPC system.

【 授权许可】

Unknown