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.
|Title of host publication||High Performance Computing - 32nd International Conference, ISC High Performance 2017, Proceedings|
|Editors||Julian M. Kunkel, Pavan Balaji, David Keyes, Rio Yokota|
|Number of pages||18|
|Publication status||Published - 2017|
|Event||32nd International Conference, ISC High Performance, 2017 - Frankfurt, Germany|
Duration: 18 Jun 2017 → 22 Jun 2017
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||32nd International Conference, ISC High Performance, 2017|
|Period||18/06/17 → 22/06/17|
Bibliographical noteFunding Information:
The authors would like to thank Thomas Ilsche and the Center of Information Services and High Performance Computing (ZIH) at TU Dresden. This research is funded in part by research grants from AWE, ATOS and Allinea. Professor Stephen Jarvis is an AWE William Penney Fellow.
© Springer International Publishing AG 2017.
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)