LMS-based low-complexity game workload prediction for DVFS

Benedikt Dietrich, Swaroop Nunna, Dip Goswami, Samarjit Chakraborty, Matthias Gries

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

25 Citations (Scopus)

Abstract

While dynamic voltage and frequency scaling (DVFS) based power management has been widely studied for video processing, there is very little work on game power management. Recent work on proportional-integral-derivative (PID) controllers fro predicting game workload used hand-turned PID controller gains on relatively short game plays. This left open questions on the robustness of the PID controller and how sensitive the prediction quality is on the choice of the gain values, especially for long game plays involving different scenarios and scene changes. In this paper we propose a Least Mean Squares (LMS) Linear Predictor, which is a regression model commonly used for system parameter identification. Our results show that game workload variation can be estimated using a linear-in-parameters (LIP) model. This observation dramatically reduces the complexity of parameter estimation as the LMS Linear Predictor learns the relevant parameters of the model iteratively as the game progresses. The only parameter to be tuned by the system designer is the learning rate, which is relatively straightforward. Our experimental results using the LMS Linear Predictor show comparable power savings and game quality with those obtained from a highly-tuned PID controller.
Original languageEnglish
Title of host publication2010 IEEE International Conference on Computer Design
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages417-424
Number of pages8
ISBN (Electronic)978-1-4244-8937-4
ISBN (Print)978-1-4244-8936-7
DOIs
Publication statusPublished - 2010
Externally publishedYes
EventInternational Conference on Computer Design - Amsterdam, Netherlands
Duration: 3 Oct 20106 Oct 2010

Conference

ConferenceInternational Conference on Computer Design
Abbreviated titleICCD 2010
CountryNetherlands
CityAmsterdam
Period3/10/106/10/10

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  • Cite this

    Dietrich, B., Nunna, S., Goswami, D., Chakraborty, S., & Gries, M. (2010). LMS-based low-complexity game workload prediction for DVFS. In 2010 IEEE International Conference on Computer Design (pp. 417-424). Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICCD.2010.5647675