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| Content Provider | ACM Digital Library |
|---|---|
| Author | Field, Hayden Anderson, Glen Eder, Kerstin |
| Abstract | 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. |
| Starting Page | 1194 |
| Ending Page | 1199 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450324694 |
| DOI | 10.1145/2554850.2554920 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-03-24 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Energy transparency Eacof Energy-aware computing Energy profiling Abstraction |
| Content Type | Text |
| Resource Type | Article |
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