Prediction and Characterization of Application Power Use in a High-performance Computing Environment

Publication Date

2-27-2017

Document Type

Article

Organizational Units

Daniels College of Business, Business Information and Analytics

Keywords

HPC, Queueing systems, Renewable energy, Scientific computing

Abstract

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.

Publication Statement

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