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Title: Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications

Abstract

The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore how different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and executionmore » of scientific algorithms.« less

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1];  [1];  [1]; ORCiD logo [2]
+ Show Author Affiliations
  1. Univ. of Tennessee, Knoxville, TN (United States). Innovative Computing Lab
  2. Univ. of Tennessee, Knoxville, TN (United States). Innovative Computing Lab ; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Manchester (United Kingdom)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC)
OSTI Identifier:
1435180
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Concurrency and Computation. Practice and Experience
Additional Journal Information:
Journal Volume: 31; Journal Issue: 6; Journal ID: ISSN 1532-0626
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; energy efficiency; high performance computing; Intel Xeon Phi; Knights landing PAPI; performance analysis; performance counters; power efficiency

Citation Formats

Haidar, Azzam, Jagode, Heike, Vaccaro, Phil, YarKhan, Asim, Tomov, Stanimire, and Dongarra, Jack. Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications. United States: N. p., 2018. Web. doi:10.1002/cpe.4485.
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Haidar, Azzam, Jagode, Heike, Vaccaro, Phil, YarKhan, Asim, Tomov, Stanimire, & Dongarra, Jack. Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications. United States. https://doi.org/10.1002/cpe.4485
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Haidar, Azzam, Jagode, Heike, Vaccaro, Phil, YarKhan, Asim, Tomov, Stanimire, and Dongarra, Jack. Sun . "Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications". United States. https://doi.org/10.1002/cpe.4485. https://www.osti.gov/servlets/purl/1435180.
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@article{osti_1435180,
title = {Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications},
author = {Haidar, Azzam and Jagode, Heike and Vaccaro, Phil and YarKhan, Asim and Tomov, Stanimire and Dongarra, Jack},
abstractNote = {The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore how different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.},
doi = {10.1002/cpe.4485},
journal = {Concurrency and Computation. Practice and Experience},
number = 6,
volume = 31,
place = {United States},
year = {2018},
month = {3}
}
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https://doi.org/10.1002/cpe.4485
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Cited by: 19 works
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Works referenced in this record:

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    Works referencing / citing this record:

    Power-aware computing: Power-aware computing
    journal, November 2018

    • Ezzatti, Pablo; Quintana-Ortí, Enrique S.; Remón, Alfredo
    • Concurrency and Computation: Practice and Experience, Vol. 31, Issue 6
    • DOI: 10.1002/cpe.5034

    Energy-Aware High-Performance Computing: Survey of State-of-the-Art Tools, Techniques, and Environments
    journal, April 2019

    • Czarnul, Pawel; Proficz, Jerzy; Krzywaniak, Adam
    • Scientific Programming, Vol. 2019
    • DOI: 10.1155/2019/8348791

    Investigating power efficiency of mergesort
    journal, April 2019

    • Aljabri, Naif; Al-Hashimi, Muhammad; Saleh, Mostafa
    • The Journal of Supercomputing, Vol. 75, Issue 10
    • DOI: 10.1007/s11227-019-02850-5
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