Deep parameter optimisation on Android smartphones for energy minimisation

Bokhari, Mahmoud A.; Bruce, Bobby R.; Alexander, Bradley; Wagner, Markus

doi:10.1145/3067695.3082519

Cited by 25 publications

(12 citation statements)

References 21 publications

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“…Despite this, we have shown the proportional difference in energy readings between devices is consistent, and believe it is important that those working in energy optimisation research are aware of these issues. The seemingly simple task of being able to measure what is being optimised remains a significant hurdle in energy optimisation research [11] and, thus, care and consideration is needed when planning experiments. The Raspberry Pi/MAGEEC board setup is an abstract representation of 'real-world' systems, which researchers can use to gain insight into energy consumption in a manner which controlled, low cost, and easily expandable.…”

Section: Discussionmentioning

confidence: 99%

Approximate Oracles and Synergy in Software Energy Search Spaces

Bruce

Petke

Harman

et al. 2019

IIEEE Trans. Software Eng.

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Abstract-Reducing the energy consumption of software systems though optimisations techniques such as genetic improvement is gaining interest. However, efficient and effective improvement of software systems requires a better understanding of the code-change search space. One important choice practitioners have is whether to preserve the system's original output or permit approximation with each scenario having its own search space characteristics. When output preservation is a hard constraint, we report that the maximum energy reduction achievable by the modification operators is 2.69% (0.76% on average). By contrast, this figure increases dramatically to 95.60% (33.90% on average) when approximation is permitted, indicating the critical importance of approximate output quality assessment for code optimisation. We investigate synergy, a phenomenon that occurs when simultaneously applied source code modifications produce an effect greater than their individual sum. Our results reveal that 12.0% of all joint code modifications produced such a synergistic effect though 38.5% produce an antagonistic interaction in which simultaneously applied modifications are less effective than when applied individually. This highlights the need for more advanced search-based approaches.

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Section: Discussionmentioning

confidence: 99%

Approximate Oracles and Synergy in Software Energy Search Spaces

Bruce

Petke

Harman

et al. 2019

IIEEE Trans. Software Eng.

Self Cite

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“…However, it is not as accurate as other techniques, because voltage is scaled dynamically and multiple hardware components are used [161]. One should consider that errors during the measurement and estimation of energy consumption, as noise, can be introduced by various hardware components, such as a rising temperature of the battery [165]. This impacts the number of samples required for ensuring statistical significance when comparing the energy consumption of applications [166].…”

Section: Profilingmentioning

confidence: 99%

“…Mutation operations were applied to the source code of a Boolean satisfiability solver, to reduce energy consumption as a measure of fitness. Bokhari et al [165] applied approximate computing on Rebound, 11 a Java Physics library, to achieve a trade-off between accuracy and energy consumption.…”

Section: Optimization Approachesmentioning

confidence: 99%

A Survey of Performance Optimization for Mobile Applications

Hort

Kechagia

Sarro

et al. 2022

IIEEE Trans. Software Eng.

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To ensure user satisfaction and success of mobile applications, it is important to provide highly performant applications. This is particularly important for resource-constrained systems such as mobile devices. Thereby, non-functional performance characteristics, such as energy and memory consumption, play an important role for user satisfaction. This paper provides a comprehensive survey of non-functional performance optimization for Android applications. We collected 156 unique publications, published between 2008 and 2020, that focus on the optimization of performance of mobile applications. We target our search at four performance characteristics: responsiveness, launch time, memory and energy consumption. For each performance characteristic, we categorize optimization approaches based on the method used in the corresponding publications. Furthermore, we identify research gaps in the literature for future work.

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“…The current version of the GNU C library, glibc-2.29, was downloaded 2 . The table driven powerPC version of sqrt.c uses the format of double precision numbers ( Figure 3).…”

Section: Existing Newton-raphson Calculation Of Sqrtmentioning

confidence: 99%