Metrics for energy-aware software optimisation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Metrics for energy-aware software optimisation. / Roberts, Stephen I.; Wright, Steven A.; Fahmy, Suhaib A.; Jarvis, Stephen A.

High Performance Computing - 32nd International Conference, ISC High Performance 2017, Proceedings. Vol. 10266 LNCS Springer-Verlag, 2017. p. 413-430 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10266 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Roberts, SI, Wright, SA, Fahmy, SA & Jarvis, SA 2017, Metrics for energy-aware software optimisation. in High Performance Computing - 32nd International Conference, ISC High Performance 2017, Proceedings. vol. 10266 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10266 LNCS, Springer-Verlag, pp. 413-430, 32nd International Conference, ISC High Performance, 2017, Frankfurt, Germany, 18/06/17. https://doi.org/10.1007/978-3-319-58667-0_22

APA

Roberts, S. I., Wright, S. A., Fahmy, S. A., & Jarvis, S. A. (2017). Metrics for energy-aware software optimisation. In High Performance Computing - 32nd International Conference, ISC High Performance 2017, Proceedings (Vol. 10266 LNCS, pp. 413-430). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10266 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-319-58667-0_22

Vancouver

Roberts SI, Wright SA, Fahmy SA, Jarvis SA. Metrics for energy-aware software optimisation. In High Performance Computing - 32nd International Conference, ISC High Performance 2017, Proceedings. Vol. 10266 LNCS. Springer-Verlag. 2017. p. 413-430. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-58667-0_22

Author

Roberts, Stephen I. ; Wright, Steven A. ; Fahmy, Suhaib A. ; Jarvis, Stephen A. / Metrics for energy-aware software optimisation. High Performance Computing - 32nd International Conference, ISC High Performance 2017, Proceedings. Vol. 10266 LNCS Springer-Verlag, 2017. pp. 413-430 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Bibtex - Download

@inproceedings{089b5d21d7e24486ba50b177df2ab49f,
title = "Metrics for energy-aware software optimisation",
abstract = "Energy consumption is rapidly becoming a limiting factor in scientific computing. As a result, hardware manufacturers increasingly prioritise energy efficiency in their processor designs. Performance engineers are also beginning to explore software optimisation and hardware/software co-design as a means to reduce energy consumption. Energy efficiency metrics developed by the hardware community are often re-purposed to guide these software optimisation efforts. In this paper we argue that established metrics, and in particular those in the Energy Delay Product (Etn) family, are unsuitable for energyaware software optimisation. A good metric should provide meaningful values for a single experiment, allow fair comparison between experiments, and drive optimisation in a sensible direction. We show that Etn metrics are unable to fulfil these basic requirements and present suitable alternatives for guiding energy-aware software optimisation. We finish with a practical demonstration of the utility of our proposed metrics.",
author = "Roberts, {Stephen I.} and Wright, {Steven A.} and Fahmy, {Suhaib A.} and Jarvis, {Stephen A.}",
note = "{\textcopyright} Springer International Publishing AG 2017. This is an author-produced version of the published paper. Uploaded in accordance with the publisher{\textquoteright}s self-archiving policy. Further copying may not be permitted; contact the publisher for details.; 32nd International Conference, ISC High Performance, 2017 ; Conference date: 18-06-2017 Through 22-06-2017",
year = "2017",
month = may,
day = "12",
doi = "10.1007/978-3-319-58667-0_22",
language = "English",
isbn = "9783319586663",
volume = "10266 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "413--430",
booktitle = "High Performance Computing - 32nd International Conference, ISC High Performance 2017, Proceedings",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Metrics for energy-aware software optimisation

AU - Roberts, Stephen I.

AU - Wright, Steven A.

AU - Fahmy, Suhaib A.

AU - Jarvis, Stephen A.

N1 - © Springer International Publishing AG 2017. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

PY - 2017/5/12

Y1 - 2017/5/12

N2 - Energy consumption is rapidly becoming a limiting factor in scientific computing. As a result, hardware manufacturers increasingly prioritise energy efficiency in their processor designs. Performance engineers are also beginning to explore software optimisation and hardware/software co-design as a means to reduce energy consumption. Energy efficiency metrics developed by the hardware community are often re-purposed to guide these software optimisation efforts. In this paper we argue that established metrics, and in particular those in the Energy Delay Product (Etn) family, are unsuitable for energyaware software optimisation. A good metric should provide meaningful values for a single experiment, allow fair comparison between experiments, and drive optimisation in a sensible direction. We show that Etn metrics are unable to fulfil these basic requirements and present suitable alternatives for guiding energy-aware software optimisation. We finish with a practical demonstration of the utility of our proposed metrics.

AB - Energy consumption is rapidly becoming a limiting factor in scientific computing. As a result, hardware manufacturers increasingly prioritise energy efficiency in their processor designs. Performance engineers are also beginning to explore software optimisation and hardware/software co-design as a means to reduce energy consumption. Energy efficiency metrics developed by the hardware community are often re-purposed to guide these software optimisation efforts. In this paper we argue that established metrics, and in particular those in the Energy Delay Product (Etn) family, are unsuitable for energyaware software optimisation. A good metric should provide meaningful values for a single experiment, allow fair comparison between experiments, and drive optimisation in a sensible direction. We show that Etn metrics are unable to fulfil these basic requirements and present suitable alternatives for guiding energy-aware software optimisation. We finish with a practical demonstration of the utility of our proposed metrics.

UR - http://www.scopus.com/inward/record.url?scp=85026266811&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-58667-0_22

DO - 10.1007/978-3-319-58667-0_22

M3 - Conference contribution

AN - SCOPUS:85026266811

SN - 9783319586663

VL - 10266 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 413

EP - 430

BT - High Performance Computing - 32nd International Conference, ISC High Performance 2017, Proceedings

PB - Springer-Verlag

T2 - 32nd International Conference, ISC High Performance, 2017

Y2 - 18 June 2017 through 22 June 2017

ER -