Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/2392987.2392997acmotherconferencesArticle/Chapter ViewAbstractPublication PagesrtnsConference Proceedingsconference-collections
research-article

Analytical leakage/temperature-aware power modeling and optimization for a variable speed real-time system

Published: 08 November 2012 Publication History

Abstract

We consider a DVS-enabled single-processor firm real-time (FRT) system with Poisson arrival jobs having exponential execution times and generally distributed relative deadlines. The queue size of the system bounds the number of jobs which may be available therein. Further, the processor speed depends on the number of jobs in the system which varies because of the job arrivals, service completions, and deadline misses. Thus, the processor power consumption, including both the dynamic and leakage powers, depends on the stochastic nature of the system. More specifically, the instantaneous dynamic power consumption lonely depends on the number of jobs at that moment. However, the instantaneous leakage power consumption depends on both the number of jobs and the instantaneous processor temperature. In turn, the temperature is affected by both the dynamic and leakage power consumptions. Taking all the aforementioned inter-effects into account, this paper analytically models the timing, power and temperature behaviors of such a variable speed FRT system. The analysis is then employed to address the problem of the system average power (and thus, energy) minimization subject to guaranteeing some upper bound on the system loss probability. Simulation results are also put against the analytical ones to show the accuracy level of the proposed analytical method as well as the efficacy of the optimizations.

Supplementary Material

JPG File (p81-mohaqeqi.jpg)
Optimal power for different loss probability thresholds

References

[1]
Y. Ahn. Real-time task scheduling under thermal constraints. PhD thesis, TEXAS A&M UNIVERSITY, 2010.
[2]
D. Barrer. Queuing with impatient customers and ordered service. Operations Research, 5(5):650--656, 1957.
[3]
G. Bernat, A. Burns, and A. Llamosi. Weakly hard real-time systems. IEEE Trans. Comput., 50(4):308--321, Apr. 2001.
[4]
A. Brandt and M. Brandt. Asymptotic results and a markovian approximation for the m (n) /m (n) /s+gi system. Queueing Systems, 41(1):73--94, 2002.
[5]
V. Chaturvedi, H. Huang, and G. Quan. Leakage aware scheduling on maximum temperature minimization for periodic hard real-time systems. In Proceedings of the 2010 10th IEEE International Conference on Computer and Information Technology, CIT '10, pages 1802--1809, Washington, DC, USA, 2010. IEEE Computer Society.
[6]
V. Chaturvedi and G. Quan. Leakage conscious dvs scheduling for peak temperature minimization. In Design Automation Conference (ASP-DAC), 2011 16th Asia and South Pacific, pages 135--140, jan. 2011.
[7]
J. Chen, H. Hsu, and T. Kuo. Leakage-aware energy-efficient scheduling of real-time tasks in multiprocessor systems. In Real-Time and Embedded Technology and Applications Symposium, 2006. Proceedings of the 12th IEEE, pages 408--417. IEEE, 2006.
[8]
N. Fisher, J.-J. Chen, S. Wang, and L. Thiele. Thermal-aware global real-time scheduling and analysis on multicore systems. Journal of Systems Architecture, 57(5):547--560, 2011.
[9]
H. Huang and G. Quan. Leakage aware energy minimization for real-time systems under the maximum temperature constraint. In Design, Automation Test in Europe Conference Exhibition (DATE), 2011, pages 1--6, march 2011.
[10]
R. Jejurikar and R. Gupta. Dynamic slack reclamation with procrastination scheduling in real-time embedded systems. In Proceedings of the 42nd annual Design Automation Conference, pages 111--116. ACM, 2005.
[11]
H. Jung, P. Rong, and M. Pedram. Stochastic modeling of a thermally-manage multi-core system. In Proceedings of the 45th annual Design Automation Conference, DAC '08, pages 728--733, New York, NY, USA, 2008. ACM.
[12]
M. Kargahi and A. Movaghar. Non-preemptive earliest-deadline-first scheduling policy: a performance study. In Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, 2005. 13th IEEE International Symposium on, pages 201--208. IEEE, 2005.
[13]
M. Kargahi and A. Movaghar. A method for performance analysis of earliest-deadline-first scheduling policy. The Journal of Supercomputing, 37(2):197--222, 2006.
[14]
M. Kargahi and A. Movaghar. Stochastic dvs-based dynamic power management for soft real-time systems. Microprocessors and Microsystems, 32(3):121--144, 2008.
[15]
M. Kargahi and A. Movaghar. Performance optimization based on analytical modeling in a real-time system with constrained time/utility functions. Computers, IEEE Transactions on, 60(8):1169--1181, aug. 2011.
[16]
J. P. Lehoczky. Real-time queueing theory. In IEEE Real-Time Systems Symposium, pages 186--195, 1996.
[17]
J. P. Lehoczky. Real-time queueing network theory. In IEEE Real-Time Systems Symposium, pages 58--67, 1997.
[18]
W. Liao, L. He, and K. Lepak. Temperature and supply voltage aware performance and power modeling at microarchitecture level. Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on, 24(7):1042--1053, july 2005.
[19]
Y. Liu, R. Dick, L. Shang, and H. Yang. Accurate temperature-dependent integrated circuit leakage power estimation is easy. In Proceedings of the conference on Design, automation and test in Europe, pages 1526--1531. EDA Consortium, 2007.
[20]
M. Mohaqeqi, M. Kargahi, and A. Movaghar. Analytical leakage-aware thermal modeling of a real-time system. Computers, IEEE Transactions on, to appear.
[21]
C. Moser, L. Thiele, D. Brunelli, and L. Benini. Robust and low complexity rate control for solar powered sensors. In Proceedings of the conference on Design, automation and test in Europe, DATE '08, pages 230--235, New York, NY, USA, 2008. ACM.
[22]
A. Movaghar. On queuing with customer impatience until the end of service. The Journal of Stochastic Models, 22:149--173, 2006.
[23]
S. Park, J.-J. Chen, D. Shin, Y. Kim, C.-L. Yang, and N. Chang. Dynamic thermal management for networked embedded systems under harsh ambient temperature variation. In Low-Power Electronics and Design (ISLPED), 2010 ACM/IEEE International Symposium on, pages 289--294, aug. 2010.
[24]
G. Quan and V. Chaturvedi. Feasibility analysis for temperature-constraint hard real-time periodic tasks. Industrial Informatics, IEEE Transactions on, 6(3):329--339, aug. 2010.
[25]
G. Quan and Y. Zhang. Leakage aware feasibility analysis for temperature-constrained hard real-time periodic tasks. In Proceedings of the 2009 21st Euromicro Conference on Real-Time Systems, pages 207--216, Washington, DC, USA, 2009. IEEE Computer Society.
[26]
J. Rabaey, A. Chandrakasan, and B. Nikolic. Digital integrated circuits: a design perspective. Prentice Hall electronics and VLSI series. Pearson Education, 2003.
[27]
R. Rao and S. Vrudhula. Fast and accurate prediction of the steady-state throughput of multicore processors under thermal constraints. Trans. Comp.-Aided Des. Integ. Cir. Sys., 28(10):1559--1572, Oct. 2009.
[28]
K. Skadron, T. Abdelzaher, and M. Stan. Control-theoretic techniques and thermal-rc modeling for accurate and localized dynamic thermal management. In High-Performance Computer Architecture, 2002. Proceedings. Eighth International Symposium on, pages 17--28, feb. 2002.
[29]
A. Wierman, L. Andrew, and A. Tang. Stochastic analysis of power-aware scheduling. In Communication, Control, and Computing, 2008 46th Annual Allerton Conference on, pages 1278--1283. IEEE, 2008.
[30]
M. Wiggers, M. Bekooij, P. Jansen, and G. Smit. Efficient computation of buffer capacities for multi-rate real-time systems with back-pressure. In Hardware/Software Codesign and System Synthesis, 2006. CODES+ISSS '06. Proceedings of the 4th International Conference, pages 10--15, oct. 2006.
[31]
C. Yang, J. Chen, L. Thiele, and T. Kuo. Energy-efficient real-time task scheduling with temperature-dependent leakage. In Proceedings of the Conference on Design, Automation and Test in Europe, pages 9--14. European Design and Automation Association, 2010.
[32]
L. Yuan, S. Leventhal, and G. Qu. Temperature-aware leakage minimization technique for real-time systems. In Computer-Aided Design, 2006. ICCAD '06. IEEE/ACM International Conference on, pages 761--764, nov. 2006.

Cited By

View all
  • (2018)Thermal analysis of stochastic DVFS-enabled multicore real-time systemsThe Journal of Supercomputing10.1007/s11227-015-1562-171:12(4594-4622)Online publication date: 31-Dec-2018
  • (2016)Stochastic Thermal Control of a Multicore Real-Time System2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)10.1109/PDP.2016.44(208-215)Online publication date: Feb-2016
  • (2015)Joint management of processing and cooling power based on inaccurate thermal information in a stochastic real-time systemProceedings of the 23rd International Conference on Real Time and Networks Systems10.1145/2834848.2834879(45-54)Online publication date: 4-Nov-2015
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences
RTNS '12: Proceedings of the 20th International Conference on Real-Time and Network Systems
November 2012
216 pages
ISBN:9781450314091
DOI:10.1145/2392987
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]

Sponsors

  • University of Lorraine: University of Lorraine
  • INRIA: Institut Natl de Recherche en Info et en Automatique
  • GDR ASR: GDR Architecture, Systèmes et Réseaux

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 November 2012

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Markov model
  2. dynamic voltage scaling
  3. leakage-aware power optimization
  4. real-time systems
  5. temperature-aware power management

Qualifiers

  • Research-article

Conference

RTNS '12
Sponsor:
  • University of Lorraine
  • INRIA
  • GDR ASR

Acceptance Rates

Overall Acceptance Rate 119 of 255 submissions, 47%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)0
Reflects downloads up to 19 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2018)Thermal analysis of stochastic DVFS-enabled multicore real-time systemsThe Journal of Supercomputing10.1007/s11227-015-1562-171:12(4594-4622)Online publication date: 31-Dec-2018
  • (2016)Stochastic Thermal Control of a Multicore Real-Time System2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)10.1109/PDP.2016.44(208-215)Online publication date: Feb-2016
  • (2015)Joint management of processing and cooling power based on inaccurate thermal information in a stochastic real-time systemProceedings of the 23rd International Conference on Real Time and Networks Systems10.1145/2834848.2834879(45-54)Online publication date: 4-Nov-2015
  • (2013)Thermal analysis of periodic real-time systems with stochastic propertiesProceedings of the 21st International conference on Real-Time Networks and Systems10.1145/2516821.2516846(119-127)Online publication date: 16-Oct-2013

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media