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Title: Prediction and characterization of application power use in a high-performance computing environment

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. Lastly, we highlight a potential use case of this method through a simulated power-aware scheduler using historical jobs from a real scientific HPC system.
Authors:
 [1] ;  [1] ;  [2] ;  [3] ;  [1] ;  [1]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Univ. of Colorado, Boulder, CO (United States)
  3. Univ. of Denver, Denver, CO (United States)
Publication Date:
Report Number(s):
NREL/JA-2C00-67863
Journal ID: ISSN 1932-1864
Grant/Contract Number:
AC36-08GO28308; 1503672
Type:
Accepted Manuscript
Journal Name:
Statistical Analysis and Data Mining
Additional Journal Information:
Journal Volume: 10; Journal Issue: 3; Journal ID: ISSN 1932-1864
Publisher:
Wiley
Research Org:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; HPC; queueing systems; renewable energy; scientific computing
OSTI Identifier:
1361232
Alternate Identifier(s):
OSTI ID: 1400847