Data Dependent Energy Modeling for Worst Case Energy Consumption Analysis

Pallister, James, Kerrison, Steve, Morse, Jeremy, and Eder, Kerstin (2017) Data Dependent Energy Modeling for Worst Case Energy Consumption Analysis. In: Proceedings of the 20th International Workshop on Software and Compilers for Embedded Systems. pp. 51-59. From: SCOPES '17: 20th International Workshop on Software and Compilers for Embedded Systems, 12-13 June 2017, Sankt Goar, Germany.

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DOI: 10.1145/3078659.3078666

View at Publisher Website: https://doi.org/10.1145/3078659.3078666

Abstract

Safely meeting Worst Case Energy Consumption (WCEC) criteria requires accurate energy modeling of software. We investigate the impact of instruction operand values upon energy consumption in cacheless embedded processors. Existing instruction-level energy models typically use measurements from random input data, providing estimates unsuitable for safe WCEC analysis.

We examine probabilistic energy distributions of instructions and propose a model for composing instruction sequences using distributions, enabling WCEC analysis on program basic blocks. The worst case is predicted with statistical analysis. Further, we verify that the energy of embedded benchmarks can be characterised as a distribution, and compare our proposed technique with other methods of estimating energy consumption.


Item ID:	68086
Item Type:	Conference Item (Research - E1)
ISBN:	9781450350396
Copyright Information:	© 2017 Copyright held by the owner/author(s). Publication rights licensed to Association for Computing Machinery
Date Deposited:	24 Mar 2025 02:52
FoR Codes:	46 INFORMATION AND COMPUTING SCIENCES > 4612 Software engineering > 461208 Software testing, verification and validation @ 50% 46 INFORMATION AND COMPUTING SCIENCES > 4612 Software engineering > 461207 Software quality, processes and metrics @ 50%
SEO Codes:	17 ENERGY > 1701 Energy efficiency > 170102 Industrial energy efficiency @ 50% 22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220401 Application software packages @ 50%
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