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Power Consumption Profiling of a Lightweight Development Board: Sensing with the INA219 and Teensy 4.0 Microcontroller

Lambert, Jonathan, Monahan, Rosemary and Casey, Kevin (2021) Power Consumption Profiling of a Lightweight Development Board: Sensing with the INA219 and Teensy 4.0 Microcontroller. Electronics, 10 (7). p. 775. ISSN 2079-9292

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Official URL: https://doi.org/10.3390/electronics10070775

Abstract

At the heart of most technological advancements is a network of processors executing code and consuming energy. Understanding those systems’ energy consumption profiles provides optimisation possibilities and thus contributes to strategies for reducing energy consumption in general. This paper assesses the power consumption characteristics of a highly competitive low cost, small form factor development board (the Raspberry Pi4 model B), powered with the minimal load associated with its bare-metal configuration and the related impact on baseline power consumption. We also consider the load associated with an out-of-box operating system, running at several underclocking frequency scaling levels and the associated impact on baseline power consumption. Our experimental set-up consists of integrating an INA219 high-side current sense amplifier for the capturing of power, current, and voltage measurements; and a Teensy 4.0 microcontroller for sampling. Overall, our results indicate statistically significant differences in overall power consumption distribution characteristics across all models. Our results also indicate the presence of three distinct power phase envelopes and statistically significant differences in mean and median power measurements between the different underclocking frequency test cases and the bare-metal cases. Our results also indicate that power consumption is an increasing monotonic function across test scenarios. Finally, our results have also shown that isolating power consumption composite distributions increases model predictability from 67% to 97%.
Keywords: computing system performance analysis; energy, power, current, and voltage consumption; current sense amplification; CPU underclocking; INA219; Raspberry Pi4 model B

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electricity Supply
Divisions: School of Computing > Staff Research and Publications
Depositing User: Dan English
Date Deposited: 26 Mar 2021 10:40
Last Modified: 26 Mar 2021 10:42
URI: http://norma.ncirl.ie/id/eprint/4810

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