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Towards better CPU power management on multicore smartphones

Published: 03 November 2013 Publication History

Abstract

Although multicore smartphones have become increasingly mainstream, it is unclear whether and how smartphone applications can utilize multicore CPUs to improve performance. In this paper we study the performance of mobile applications using multicore CPUs, in terms of power and computation cost. Using Web browsing as an example, our preliminary measurement results show that even large applications like Web browsers with multi-threading acceleration cannot fully utilize the multicore CPUs. Furthermore, we find that the existing CPU power models on smartphones are ill-suited for modern multicore CPUs. We develop a new CPU power model with a high accuracy, 95.6% on average. Our work helps to better understand the performance of multicore smartphones and paves the way towards better CPU power management on multicore smartphones.

References

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[2]
C. J. Jones, R. Liu, L. Meyerovich, K. Asanovic, and R. Bodik, "Parallelizing the Web Browser", in USENIX HotPar 2009.
[3]
C. Badea, M. R. Haghighat, A. Nicolau, and A. V. Veidenbaum, "Towards Parallelizing the Layout Engine of Firefore", in USENIX HotPar 2010.
[4]
H. Mai, S. Tang, S. T. King, C. Cascaval, and P. Montesinos, "A Case for Parallelizing Web Pages", in USENIX HotPar 2012.
[5]
F. Xu, Y. Liu, Q. Li, and Y. Zhang, "V-edge: Fast Self-constructive Power Modeling of Smartphones Based on Battery Voltage Dynamics", in USENIX NSDI 2013.
[6]
L. Zhang, B. Tiwana, Z. Qian, Z. Wang, R. Dick, Z. Mao, and L. Yang, "Accurate Online Power Estimation and Automatic Battery Behavior Based Power Model Generation for Smartphones", in CODES+ISSS, 2010.
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C. Yoon, D. Kim, W. Jung, C. Kang, and H. Cha, "Appscope: Application Energy Metering Framework for Android Smartphone Using Kernel Activity Monitoring", in USENIX ATC, 2012.
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Monsoon Power Monitor, http://www.msoon.com/LabEquipment/PowerMonitor/.
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M. Dong, and L. Zhong, "Self-constructive High-rate System Energy Modeling for Battery-powered Mobile Systems", in MobiSys, 2011.
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  • (2022)Schedulability Analysis for Coscheduling Real-Time Tasks on MultiprocessorsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.314197141:11(4721-4732)Online publication date: Nov-2022
  • (2022)HUNTERJournal of Systems and Software10.1016/j.jss.2021.111124184:COnline publication date: 1-Feb-2022
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    cover image ACM Conferences
    HotPower '13: Proceedings of the Workshop on Power-Aware Computing and Systems
    November 2013
    66 pages
    ISBN:9781450324588
    DOI:10.1145/2525526
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 03 November 2013

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    Author Tags

    1. multicore
    2. power management
    3. power modeling
    4. smartphone

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    • (2023)A Comparative Study Between External USB and MIPI CSI for Medical Imaging and a Device Driver Implementation for Endoscope Camera Using USB2023 4th International Conference on Communication, Computing and Industry 6.0 (C216)10.1109/C2I659362.2023.10430494(1-5)Online publication date: 15-Dec-2023
    • (2022)Schedulability Analysis for Coscheduling Real-Time Tasks on MultiprocessorsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.314197141:11(4721-4732)Online publication date: Nov-2022
    • (2022)HUNTERJournal of Systems and Software10.1016/j.jss.2021.111124184:COnline publication date: 1-Feb-2022
    • (2022)Evaluating System Identification Methods for Predicting Thermal Dissipation of Heterogeneous SoCsEmbedded Computer Systems: Architectures, Modeling, and Simulation10.1007/978-3-031-04580-6_10(144-160)Online publication date: 27-Apr-2022
    • (2021)Modeling of Multi-Core CPU Power Consumption during Online Video Conference2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)10.1109/IDAACS53288.2021.9660941(640-646)Online publication date: 22-Sep-2021
    • (2021)Enabling Fast Exploration and Validation of Thermal Dissipation Requirements for Heterogeneous SoCs2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)10.1109/ICSTW52544.2021.00030(114-123)Online publication date: Apr-2021
    • (2020)Diagnostics of Power Consumption of a Mobile Device Multi-Core Processor with Detail of Each Core Utilization2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET)10.1109/TCSET49122.2020.235456(368-372)Online publication date: Feb-2020
    • (2019)Understanding the impact of number of CPU cores on user satisfaction in smartphonesProceedings of the 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/3360774.3360816(288-297)Online publication date: 12-Nov-2019
    • (2019)Using Built-In Sensors to Predict and Utilize User Satisfaction for CPU Settings on SmartphonesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33144083:1(1-25)Online publication date: 29-Mar-2019
    • (2019)Collaborative Power Management Through Knowledge Sharing Among Multiple DevicesIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2018.283713138:7(1203-1215)Online publication date: Jul-2019
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