Event-based application modeling for analysis of asymmetric multicore-based mobile systems

Abstract In this paper, we suggest a generalized application model that can be utilized to support system-level execution behavior analysis of up-to-date and future mobile systems, and propose a new method (kernel event-based application modeling; KAM.2) that extracts the Android application models that are independent of processor configuration and system-management policies. To completely describe the dynamic behavior of a target application, KAM.2 analyzes the kernel events that are obtained when it is running on the system, instead of statically analyzing its source code. This analysis enables extraction of models of real-world applications, source code of which is generally not available. We validated the effectiveness of KAM.2 on a commercial smartphone with real-world applications including user-interactive ones. The runtime overhead incurred by kernel tracing was 0.29%. In terms of core utilization, KAM.2 exhibited 2.58% of mean absolute errors on average and 0.93 of Pearson correlation coefficients on average. These results demonstrate that KAM.2 extracts reliable and realistic Android application models. Also, it was found that the application model extracted using KAM.2 is independent of processor configuration and system-management policies. Therefore, KAM.2 enables practical and flexible analysis of the dynamic behavior of recent and future mobile systems.

[1]  Rizos Sakellariou,et al.  Compiler Synthesis of Task Graphs for Parallel Program Performance Prediction , 2000, LCPC.

[2]  Massoud Pedram,et al.  Dynamic voltage and frequency scaling based on workload decomposition , 2004, Proceedings of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758).

[3]  Robert P. Dick,et al.  Automatic run-time extraction of communication graphs from multithreaded applications , 2006, Proceedings of the 4th International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS '06).

[4]  Todd D. Millstein,et al.  RERAN: Timing- and touch-sensitive record and replay for Android , 2013, 2013 35th International Conference on Software Engineering (ICSE).

[5]  Geoff V. Merrett,et al.  Accurate and Stable Run-Time Power Modeling for Mobile and Embedded CPUs , 2017, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[6]  Chandandeep Singh Pabla Completely fair scheduler , 2009 .

[7]  Yao Guo,et al.  Freeze It If You Can: Challenges and Future Directions in Benchmarking Smartphone Performance , 2017, HotMobile.

[8]  Sangyoung Park,et al.  Web browser workload characterization for power management on HMP platforms , 2016, 2016 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

[9]  Michel Dagenais,et al.  Wait Analysis of Distributed Systems Using Kernel Tracing , 2016, IEEE Transactions on Parallel and Distributed Systems.

[10]  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).

[11]  An-Yeu Wu,et al.  RC-Based Temperature Prediction Scheme for Proactive Dynamic Thermal Management in Throttle-Based 3D NoCs , 2015, IEEE Transactions on Parallel and Distributed Systems.

[12]  Yuankun Xue,et al.  Scalable and realistic benchmark synthesis for efficient NoC performance evaluation: A complex network analysis approach , 2016, 2016 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

[13]  Anuj Pathania,et al.  Power-performance modelling of mobile gaming workloads on heterogeneous MPSoCs , 2015, 2015 52nd ACM/EDAC/IEEE Design Automation Conference (DAC).

[14]  Cheol Hong Kim,et al.  Measuring Variance between Smartphone Energy Consumption and Battery Life , 2014, Computer.

[15]  Abdel Ejnioui,et al.  Control and data flow graph extraction for high-level synthesis , 2004, IEEE Computer Society Annual Symposium on VLSI.

[16]  Sandip Kundu,et al.  On runtime task graph extraction in MPSoC , 2013, 2013 IEEE Computer Society Annual Symposium on VLSI (ISVLSI).

[17]  Hojung Cha,et al.  DevScope: a nonintrusive and online power analysis tool for smartphone hardware components , 2012, CODES+ISSS.

[18]  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).

[19]  Muhammad Shafique,et al.  Power management for mobile games on asymmetric multi-cores , 2015, 2015 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED).

[20]  Trevor N. Mudge,et al.  Full-System Critical Path Analysis , 2008, ISPASS 2008 - IEEE International Symposium on Performance Analysis of Systems and software.

[21]  Lei Yang,et al.  Accurate online power estimation and automatic battery behavior based power model generation for smartphones , 2010, 2010 IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

[22]  Niraj K. Jha,et al.  Task graph extraction for embedded system synthesis , 2003, 16th International Conference on VLSI Design, 2003. Proceedings..

[23]  Young Hwan Kim,et al.  Profiling-based task graph extraction on multiprocessor system-on-chip , 2016, 2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS).