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Metrics for Energy-Aware Software Optimisation
Conference proceeding   Peer reviewed

Metrics for Energy-Aware Software Optimisation

Stephen I. Roberts, Steven A. Wright, Suhaib A. Fahmy and Stephen A. Jarvis
HIGH PERFORMANCE COMPUTING (ISC HIGH PERFORMANCE 2017), Vol.10266, pp.413-430
Lecture Notes in Computer Science
01/01/2017

Abstract

Computer Science Computer Science, Theory & Methods Science & Technology Technology
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 (Et-n) 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 Et-n 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.

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