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

Journal Article · Thu Dec 06 00:00:00 EST 2018 · Sustainable Computing

DOI:https://doi.org/10.1016/j.suscom.2018.11.005· OSTI ID:1492363

Younge, Andrew J. ^[1]; Grant, Ryan E. ^[1]; Laros, III, James H. ^[1]; Levenhagen, Michael ^[1]; Olivier, Stephen L. ^[1]; Pedretti, Kevin ^[1]; Ward, Lee ^[1]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

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.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: AC04-94AL85000
• OSTI ID: 1492363
• Report Number(s): SAND--2018-14001J; 670864
• Journal Information: Sustainable Computing, Journal Name: Sustainable Computing Journal Issue: C Vol. 21; ISSN 2210-5379
• Publisher: Elsevier
• Country of Publication: United States
• Language: English

Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
97 MATHEMATICS AND COMPUTING
Cray
Energy efficient computing
HPC
Mini applications
Power-aware software
Supercomputing