[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.5555/996070.1009864acmconferencesArticle/Chapter ViewAbstractPublication PagesiccadConference Proceedingsconference-collections
Article

Approaching the Maximum Energy Saving on Embedded Systems with Multiple Voltages

Published: 09 November 2003 Publication History

Abstract

Dynamic voltage scaling (DVS) is arguably the most effectiveenergy reduction technique. The multiple-voltage DVS systems,which can operate only at pre-determined discrete voltages, arepractical and have been well studied. However, one importantunsolved problem is how many levels and at which values shouldvoltages be implemented on a multiple-voltage DVS system toachieve the maximum energy saving. We refer this as the voltageset-up problem. In this paper, (1) we derive analytical solutionsfor dual-voltage system. (2) For the general case that does nothave analytic solutions, we develop efficient numerical methods.(3) We demonstrate how to apply the proposed algorithms onsystem design. (4) Interestingly, the experimental results suggestthat the multiple-voltage DVS system, when the voltages are setup properly, can reach DVS techniqueýs full potential in energysaving. Specifically, on the design of an ad hoc application-specificsystem and the design of the MPEG video encoder, wefind that the best single-voltage systems consume 150% and 20%more energy than the tight theoretical lower bounds, respectively.However, our approach gives dual-, 3-, and 4-voltage DVS systemsettings that are only 17.6%, 4.9%, and 2.6% for the ad hocsystem, and 4.0%, 1.1%, and 0.2% for the MPEG video encoder,over the same lower bounds.

References

[1]
{1} T. D. Burd, T. A. Pering, A. J. Stratakos, and R. W. Brodersen. A dynamic voltage scaled microprocessor system. IEEE J. Solid-State Circuits, 35(11):1571-1580, Nov. 2000.
[2]
{2} A. Chandrakasan, S. Sheng, and R.W. Brodersen, Low-power CMOS digital design. IEEE J. Solid-State Circuits, 27(4):473-484, Apr. 1992.
[3]
{3} J.-M. Chang and M. Pedram. Energy minimization using multiple supply voltages. ISLPED, pp. 157-162, 1996.
[4]
{4} A. Chandrakasan, V. Gutnik, and T. Xanthopoulos. Data driven signal processing: an approach for energy efficient computing. ISLPED, pp. 347-352, 1996.
[5]
{5} C. Chen and M. Sarrafzadeh. Provably good algorithm for low power consumption with dual supply voltages. ICCAD, pp. 76-79, 1999.
[6]
{6} S. Dhar and D. Maksimovic. Low-power digital filtering using multiple voltage distribution and adaptive voltage scaling. ISLPED, pp. 207-209, 2000.
[7]
{7} S. Hua, G. Qu, and S. S. Bhattacharyya. Energy reduction techniques for multimedia applications with tolerance to deadline misses. DAC, pp. 131-136, 2003.
[8]
{8} T. Ishihara and H. Yasuura. Voltage scheduling problem for dynamically variable voltage processors. ISLPED, pp. 197- 202, 1998.
[9]
{9} M. C. Johnson and K. Roy. Datapath scheduling with multiple supply voltages and level converters. ACM Trans. on Design Automation of Electronics Systems, 2(3):227-248, 1997.
[10]
{10} A. Kalavade and P. Moghe. A tool for performance estimation of networked embedded end-systems. DAC, pp. 257- 262, 1998.
[11]
{11} G. Qu and M. Potkonjak. Techniques for energy minimization of communication pipelines. ICCAD, pp. 597-600, 1998.
[12]
{12} G. Qu. What is the limit of energy saving by dynamic voltage scaling? ICCAD, pp. 560-563, 2001.
[13]
{13} D. Mosse, H. Aydin, B. Childers, and R. Melhem. Compiler-assisted dynamic power-aware scheduling for real-time applications. COLP, 2000.
[14]
{14} S. Raje and M. Sarrafzadeh. Variable voltage scheduling. ISLPED, pp. 9-14, 1995.
[15]
{15} T. -S. Tia, Z. Deng, M. Shankar, M. Storch, J. Sun, L.-C. Wu, and J.W.-S. Liu. Probabilistic performance guarantee for real-time tasks with varying computation times. RTAS, pp. 164-173, 1995.

Cited By

View all
  • (2018)SEECSSimProceedings of the 22nd International Symposium on Distributed Simulation and Real Time Applications10.5555/3330299.3330334(263-269)Online publication date: 15-Oct-2018
  • (2018)Zero Energy Synchronization of Distributed SimulationsProceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation10.1145/3200921.3200938(85-96)Online publication date: 14-May-2018
  • (2017)Power consumption in parallel and distributed simulationsProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242235(1-15)Online publication date: 3-Dec-2017
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
ICCAD '03: Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
November 2003
899 pages
ISBN:1581137621

Sponsors

Publisher

IEEE Computer Society

United States

Publication History

Published: 09 November 2003

Check for updates

Qualifiers

  • Article

Conference

ICCAD03
Sponsor:

Acceptance Rates

ICCAD '03 Paper Acceptance Rate 129 of 490 submissions, 26%;
Overall Acceptance Rate 457 of 1,762 submissions, 26%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 09 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2018)SEECSSimProceedings of the 22nd International Symposium on Distributed Simulation and Real Time Applications10.5555/3330299.3330334(263-269)Online publication date: 15-Oct-2018
  • (2018)Zero Energy Synchronization of Distributed SimulationsProceedings of the 2018 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation10.1145/3200921.3200938(85-96)Online publication date: 14-May-2018
  • (2017)Power consumption in parallel and distributed simulationsProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242235(1-15)Online publication date: 3-Dec-2017
  • (2017)Power Efficient Distributed SimulationProceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation10.1145/3064911.3069397(77-88)Online publication date: 16-May-2017
  • (2017)Energy Efficiency Optimization for Communication of Air-Based Information Network with Guaranteed Timing ConstraintsJournal of Signal Processing Systems10.1007/s11265-016-1125-686:2-3(299-312)Online publication date: 1-Mar-2017
  • (2016)Research Challenges in Parallel and Distributed SimulationACM Transactions on Modeling and Computer Simulation10.1145/286657726:4(1-29)Online publication date: 2-May-2016
  • (2015)An Empirical Study of Energy Consumption in Distributed SimulationsProceedings of the 19th International Symposium on Distributed Simulation and Real Time Applications10.1109/DS-RT.2015.32(163-170)Online publication date: 14-Oct-2015
  • (2012)Cost Minimization with HPDFG and Data Mining for Heterogeneous DSPJournal of Signal Processing Systems10.1007/s11265-010-0546-x67:3(213-228)Online publication date: 1-Jun-2012
  • (2009)Cost minimization while satisfying hard/soft timing constraints for heterogeneous embedded systemsACM Transactions on Design Automation of Electronic Systems10.1145/1497561.149756814:2(1-30)Online publication date: 7-Apr-2009
  • (2009)An optimal solution for the heterogeneous multiprocessor single-level voltage-setup problemIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2009.202868328:11(1705-1718)Online publication date: 1-Nov-2009
  • Show More Cited By

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