SEMay 31, 2014

EACOF: A Framework for Providing Energy Transparency to enable Energy-Aware Software Development

arXiv:1406.0117v121 citationsHas Code
Originality Incremental advance
AI Analysis

This addresses the need for energy-aware software development by providing a tool to make energy data more accessible, though it is incremental as it builds on existing instrumentation methods.

The paper tackles the problem of inaccessible and incompatible energy consumption data in software development by introducing EACOF, a modular framework that abstracts energy data sources through APIs, enabling easy and portable energy profiling for developers.

Making energy consumption data accessible to software developers is an essential step towards energy efficient software engineering. The presence of various different, bespoke and incompatible, methods of instrumentation to obtain energy readings is currently limiting the widespread use of energy data in software development. This paper presents EACOF, a modular Energy-Aware Computing Framework that provides a layer of abstraction between sources of energy data and the applications that exploit them. EACOF replaces platform specific instrumentation through two APIs - one accepts input to the framework while the other provides access to application software. This allows developers to profile their code for energy consumption in an easy and portable manner using simple API calls. We outline the design of our framework and provide details of the API functionality. In a use case, where we investigate the impact of data bit width on the energy consumption of various sorting algorithms, we demonstrate that the data obtained using EACOF provides interesting, sometimes counter-intuitive, insights. All the code is available online under an open source license. http://github.com/eacof

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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