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Title: Small scale to extreme: Methods for characterizing energy efficiency in supercomputing applications

Abstract

Here, power measurement capabilities are becoming commonplace on large scale HPC system deployments. There exist several different approaches to providing power measurements that are used today, primarily in-band and out-of-band measurements. Both of these fundamental techniques can be augmented with application-level profiling and the combination of different techniques is also possible. However, it can be difficult to assess the type and detail of measurement needed to obtain insights and knowledge of the power profile of an application. In addition, the heterogeneity of modern hybrid supercomputing platforms requires that different CPU architectures must be examined as well.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1492363
Report Number(s):
SAND-2018-14001J
Journal ID: ISSN 2210-5379; 670864
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Accepted Manuscript
Journal Name:
Sustainable Computing
Additional Journal Information:
Journal Volume: 21; Journal Issue: C; Journal ID: ISSN 2210-5379
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; Supercomputing; HPC; Energy efficient computing; Mini applications; Cray; Power-aware software

Citation Formats

Younge, Andrew J., Grant, Ryan E., Laros, III, James H., Levenhagen, Michael, Olivier, Stephen L., Pedretti, Kevin, and Ward, Lee. Small scale to extreme: Methods for characterizing energy efficiency in supercomputing applications. United States: N. p., 2018. Web. doi:10.1016/j.suscom.2018.11.005.
Younge, Andrew J., Grant, Ryan E., Laros, III, James H., Levenhagen, Michael, Olivier, Stephen L., Pedretti, Kevin, & Ward, Lee. Small scale to extreme: Methods for characterizing energy efficiency in supercomputing applications. United States. doi:10.1016/j.suscom.2018.11.005.
Younge, Andrew J., Grant, Ryan E., Laros, III, James H., Levenhagen, Michael, Olivier, Stephen L., Pedretti, Kevin, and Ward, Lee. Thu . "Small scale to extreme: Methods for characterizing energy efficiency in supercomputing applications". United States. doi:10.1016/j.suscom.2018.11.005. https://www.osti.gov/servlets/purl/1492363.
@article{osti_1492363,
title = {Small scale to extreme: Methods for characterizing energy efficiency in supercomputing applications},
author = {Younge, Andrew J. and Grant, Ryan E. and Laros, III, James H. and Levenhagen, Michael and Olivier, Stephen L. and Pedretti, Kevin and Ward, Lee},
abstractNote = {Here, power measurement capabilities are becoming commonplace on large scale HPC system deployments. There exist several different approaches to providing power measurements that are used today, primarily in-band and out-of-band measurements. Both of these fundamental techniques can be augmented with application-level profiling and the combination of different techniques is also possible. However, it can be difficult to assess the type and detail of measurement needed to obtain insights and knowledge of the power profile of an application. In addition, the heterogeneity of modern hybrid supercomputing platforms requires that different CPU architectures must be examined as well.},
doi = {10.1016/j.suscom.2018.11.005},
journal = {Sustainable Computing},
number = C,
volume = 21,
place = {United States},
year = {2018},
month = {12}
}

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