Providing sustainable performance in thermally constrained mobile devices

State-of-the-art smartphones can generate excessive amounts of heat during high computational activity or long durations of use. While throttling mechanisms ensure safe component and outer skin level temperatures, frequent throttling can largely degrade the user-perceived performance. This work explores the impact of multiple different thermal constraints in a real-life smartphone on user experience. In addition to high processor temperatures, which have traditionally been a major point of interest, we show that applications can also quickly elevate battery and device skin temperatures to critical levels. We introduce and evaluate various thermally-efficient runtime management techniques that slow down heating under performance guarantees so as to sustain a desirable performance for maximum durations. Our techniques achieve up to 8x longer sustainable QoS.

[1]  Vijay Janapa Reddi,et al.  Event-based scheduling for energy-efficient QoS (eQoS) in mobile Web applications , 2015, 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA).

[2]  Onur Sahin,et al.  Just enough is more: Achieving sustainable performance in mobile devices under thermal limitations , 2015, 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

[3]  Henry Hoffmann,et al.  Dynamic knobs for responsive power-aware computing , 2011, ASPLOS XVI.

[4]  Ümit Y. Ogras,et al.  Predictive dynamic thermal and power management for heterogeneous mobile platforms , 2015, 2015 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[5]  Onur Sahin,et al.  QScale: Thermally-efficient QoS management on heterogeneous mobile platforms , 2016, 2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

[6]  Martin C. Herbordt,et al.  Software optimization for performance, energy, and thermal distribution: Initial case studies , 2011, 2011 International Green Computing Conference and Workshops.

[7]  Vijay Janapa Reddi,et al.  Mobile CPU's rise to power: Quantifying the impact of generational mobile CPU design trends on performance, energy, and user satisfaction , 2016, 2016 IEEE International Symposium on High Performance Computer Architecture (HPCA).

[8]  Muhammad Shafique,et al.  Improving mobile gaming performance through cooperative CPU-GPU thermal management , 2016, 2016 53nd ACM/EDAC/IEEE Design Automation Conference (DAC).

[9]  Woongki Baek,et al.  HARS: A heterogeneity-aware runtime system for self-adaptive multithreaded applications , 2015, 2015 52nd ACM/EDAC/IEEE Design Automation Conference (DAC).

[10]  Henry Hoffmann,et al.  Application heartbeats: a generic interface for specifying program performance and goals in autonomous computing environments , 2010, ICAC '10.

[11]  Kai Li,et al.  The PARSEC benchmark suite: Characterization and architectural implications , 2008, 2008 International Conference on Parallel Architectures and Compilation Techniques (PACT).

[12]  John L. Henning SPEC CPU2006 benchmark descriptions , 2006, CARN.

[13]  Oguz Ergin,et al.  User-specific skin temperature-aware DVFS for smartphones , 2015, 2015 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[14]  Massoud Pedram,et al.  Therminator: A thermal simulator for smartphones producing accurate chip and skin temperature maps , 2014, 2014 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED).

[15]  Xiaobo Sharon Hu,et al.  Online work maximization under a peak temperature constraint , 2009, ISLPED.