Predictive models for multimedia applications power consumption based on use-case and OS level analysis

Power management at any abstraction level is a key issue for many mobile multimedia and embedded applications. In this paper a design workflow to generate system-level power models will be presented, tailored to support quantitative run-time power optimization policies to be implemented within an operating system. The approach we followed to derive power models is strongly use-case oriented. Starting from a comprehensive general and accurate model of a representative architecture for embedded applications (including a multi core MPSoC, accelerators, interfaces and peripherals), a methodology to derive compact models is presented, based upon the distinctive characteristics of the selected use cases. The methodology to generate such model, whose exploitation is foreseen within a power manager working at the OS level, is the focus of the paper. The value and accuracy of the approach is quantitatively and statistically justified through extensive experiments carried out on a development board designed for multimedia applications.

[1]  Luca Benini,et al.  Energy characterization of embedded real-time operating systems , 2001, CARN.

[2]  Lizy Kurian John,et al.  Run-time modeling and estimation of operating system power consumption , 2003, SIGMETRICS '03.

[3]  B. Brock,et al.  Dynamic power management for embedded systems [SOC design] , 2003, IEEE International [Systems-on-Chip] SOC Conference, 2003. Proceedings..

[4]  Niraj K. Jha,et al.  Analysis of power dissipation in embedded systems using real-time operating systems , 2003, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[5]  Bruce Jacob,et al.  The Performance and Energy Consumption of Embedded Real-Time Operating Systems , 2003, IEEE Trans. Computers.

[6]  Niraj K. Jha,et al.  EMSIM: an energy simulation framework for an embedded operating system , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[7]  Rajesh K. Gupta,et al.  Dynamic voltage scaling for systemwide energy minimization in real-time embedded systems , 2004, Proceedings of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758).

[8]  Mahmut T. Kandemir,et al.  Using complete machine simulation for software power estimation: the SoftWatt approach , 2002, Proceedings Eighth International Symposium on High Performance Computer Architecture.

[9]  Chaitali Chakrabarti,et al.  Variable voltage task scheduling algorithms for minimizing energy/power , 2003, IEEE Trans. Very Large Scale Integr. Syst..

[10]  Naehyuck Chang,et al.  Memory-aware energy-optimal frequency assignment for dynamic supply voltage scaling , 2004, Proceedings of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758).

[11]  P. John Statistical Design and Analysis of Experiments , 1971 .

[12]  Bishop Brock,et al.  Dynamic Power Management for Embedded Systems , 2003 .

[13]  Linwei Niu,et al.  Reducing both dynamic and leakage energy consumption for hard real-time systems , 2004, CASES '04.

[14]  Thomas D. Burd,et al.  Voltage scheduling in the IpARM microprocessor system , 2000, ISLPED'00: Proceedings of the 2000 International Symposium on Low Power Electronics and Design (Cat. No.00TH8514).

[15]  Luca Benini,et al.  Quantitative comparison of power management algorithms , 2000, Proceedings Design, Automation and Test in Europe Conference and Exhibition 2000 (Cat. No. PR00537).

[16]  Hal Wasserman,et al.  Comparing algorithm for dynamic speed-setting of a low-power CPU , 1995, MobiCom '95.

[17]  Taewhan Kim,et al.  DC-DC converter-aware power management for battery-operated embedded systems , 2005, Proceedings. 42nd Design Automation Conference, 2005..

[18]  Chaitali Chakrabarti,et al.  High-level power management of embedded systems with application-specific energy cost functions , 2006, 2006 43rd ACM/IEEE Design Automation Conference.

[19]  Luca Benini,et al.  A survey of design techniques for system-level dynamic power management , 2000, IEEE Trans. Very Large Scale Integr. Syst..

[20]  Klara Nahrstedt,et al.  Energy-efficient soft real-time CPU scheduling for mobile multimedia systems , 2003, SOSP '03.

[21]  Niraj K. Jha,et al.  Embedded operating system energy analysis and macro-modeling , 2002, Proceedings. IEEE International Conference on Computer Design: VLSI in Computers and Processors.

[22]  Alan Jay Smith,et al.  PACE: a new approach to dynamic voltage scaling , 2004, IEEE Transactions on Computers.

[23]  Rajesh K. Gupta,et al.  Leakage aware dynamic voltage scaling for real-time embedded systems , 2004, Proceedings. 41st Design Automation Conference, 2004..

[24]  Thomas D. Burd,et al.  The simulation and evaluation of dynamic voltage scaling algorithms , 1998, Proceedings. 1998 International Symposium on Low Power Electronics and Design (IEEE Cat. No.98TH8379).

[25]  Kang G. Shin,et al.  Real-time dynamic voltage scaling for low-power embedded operating systems , 2001, SOSP.

[26]  Patricia J. Teller,et al.  Accurate measurement of system call service times for trace-driven simulation of memory hierarchy designs , 1998, 1998 IEEE International Performance, Computing and Communications Conference. Proceedings (Cat. No.98CH36191).

[27]  William Fornaciari,et al.  Measurement, Analysis and Modeling of RTOS System Calls Timing , 2008, 2008 11th EUROMICRO Conference on Digital System Design Architectures, Methods and Tools.