skip to main content
article

Power macromodeling of MPSoC message passing primitives

Published:01 September 2007Publication History
Skip Abstract Section

Abstract

Estimating the energy consumption of software in multiprocessor systems-on-chip (MPSoCs) is crucial for enabling quick evaluations of both software and hardware optimizations. However, high-level estimations should be applicable at software level, possibly constructing effective power models depending on parameters that can be extracted directly from the application characteristics. We propose a methodology for accurate analysis of power consumption of message-passing primitives in a MPSoC, and, in particular, an energy model which, in spite of its simplicity, allows to model the traffic-dependent nature of energy consumption through the use of a single, abstract parameter, namely, the size of the message exchanged.

References

  1. Aarts, E. and Roovers, R. 2003. Ic design challenges for ambient intelligence. In Proceedings of the Design, Automation and Test in Europe Conference. 2--7. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Ackland, B. et al. 2000. A single chip, 1.6 billion, 16-b mac/s multiprocessor dsp. IEEE Journal of Solid State Circuits 35, 3 (Mar.).Google ScholarGoogle ScholarCross RefCross Ref
  3. Acquaviva, A., Benini, L., and Riccò, B. 2003a. Energy characterization of embedded real-time operating systems. In Compilers and operating systems for low power. Kluwer Academic Publ., Norwell, MA. 53--73. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Acquaviva, A., Lattanzi, E., Bogliolo, A., and Benini, L. 2003b. A simulation model for streaming applications over a power manageable wireless link. In Proceedings of the European Simulation and Modeling Conference. 39--45.Google ScholarGoogle Scholar
  5. ARM11 MPCore. Arm11 mpcore. http://www.arm.com/products/CPUs/ARM11MPCoreMultiprocessor.html.Google ScholarGoogle Scholar
  6. Benini, L. and Poncino, M. 2003. Ambient intelligence: A computational platform perspective. In Ambient Intelligence: Impact on Embedded System Design. Kluwer Academic Publishers, Norwell, MA. 31--50. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Benini, L. et al. 2002. A framework for modeling and estimating the energy dissipation of vliw-based embedded systems. In Design Automation for Embedded Systems. Vol. 7. 183--203.Google ScholarGoogle Scholar
  8. Bona, A., Zaccaria, V., and Zafalon, R. 2004. System-level power modeling and simulation of high-end industrial network-on-chip. In Proceedings of DATE'04: Design Automation and Test in Europe. 318--323. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Brooks, D. et al. 2000. Power-aware micro-architecture: Design and modeling challenges for next-generation microprocessors. IEEE Micro 20, 6 (Nov.--Dec.), 24--44. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Chinosi, M., Zafalon, R., and Guardiani, C. 1998. Automatic characterization and modeling of power consumption in static rams. In Proceedings of ISLPED'98. 112--114. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Cumming, P. 2003. The TI OMAP Platform Approach to SoC. Kluwer Academic Publishers, Norwell, MA.Google ScholarGoogle Scholar
  12. Dick, R. and Jha, N. 1998. Mogac: a multi-objective genetic algorithm for hardware-software co-synthesis of distributed embedded systems. IEEE Transactions on CAD 17, 10 (Oct.), 920--935. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Dick, R., Lakshminarayana, G., Raghunathan, A., and Jha, N. 2003. Analysis of power dissipation in embedded systems using real-time operating systems. IEEE Transactions on CAD 22, 5 (May), 615--627. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Givargis, T., Vahid., F., and Henkel, J. 2002. Instruction-based system-level power evaluation of system-on-a-chip peripheral cores. IEEE Transactions on VLSI Systems 10, 6 (Dec.), 856--863. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Grammatikakis, M., Coppola, and M., Sensini, F. 2003. Software for multiprocessor networks-on-chip. In Networks on Chip. Kluwer Academic Publishers, Norwell, MA. 281--303. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Gurumurthi, S. et al. 2002. Using complete machine simulation for software power estimation: the softwatt approach. In Proceedings of the International Symposium on High-Performance Computer Architecture. 141--150. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Henkel, J. and Yanbing Li. 2002. Avalanche: an environment for design space exploration and optimization of low-power embedded systems. IEEE Transactions on VLSI Systems 10, 4 (Aug.), 454--468. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Lahiri, K., Raghunathan, A., and Dey, S. 2001. System-level performance analysis for designing on-chip communication architectures. IEEE Transactions on CAD 20, 6 (June), 768--783. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Lajolo, M., Raghunathan, A., Dey, S., and Lavagno, L. 2002. Cosimulation-based power estimation for system-on-chip design. IEEE Transactions on VLSI Systems 10, 3 (June), 253--266. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Loghi, M., Angiolini, F., Bertozzi, D., Benini, L., and Zafalon, R. 2004. Analyzing on-chip communication in a mpsoc environment. In Proceedings of DATE'04. 752--757. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Macii, E. and Poncino, M. 2004. Power macro-models for high-level power estimation. In Low Power Electronics Design. CRC Press, Boca Raton, FL.Google ScholarGoogle Scholar
  22. Muresan, R. and Gebotys, C. 2002. Current dynamics-based macro-model for power simulation in a complex vliw dsp processor. In Proceedings of IEE Computers and Digital Techniques. Vol. 149. 173--187.Google ScholarGoogle Scholar
  23. Philips Semiconductor. Philips nexperia platform. http://www.semiconductors.philips.com/products/nexperia/home.Google ScholarGoogle Scholar
  24. Richardson, S. 2002. Mpoc: A chip multiprocessor for embedded systems. HP Technical Report, HPL-2002-186.Google ScholarGoogle Scholar
  25. Richter, K., Jersak, M., and Ernst, R. 2003. A formal approach to mpsoc performance verification. IEEE Computer 36, 4 (Apr.), 60--67. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. RTEMS Home Page. Rtems home page. http://www.rtems.com.Google ScholarGoogle Scholar
  27. SiliconHive. Siliconhive. http://www.silicon-hive.com.Google ScholarGoogle Scholar
  28. Simunic, T., Benini, L., and Micheli, G. D. 2001. Energy-efficient design of battery-powered embedded systems. IEEE Transactions on Very Large-Scale Integration Systems 9, 1 (Feb.), 15--28. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Software ARM. Software arm. http://www.g141.com/projects/swarm.Google ScholarGoogle Scholar
  30. Tan, T., Raghunathan, A., and Jha, N. 2002. Embedded operating system energy analysis and macro-modeling. In Proceedings of the International Conference on Computer Design. 515--222. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Tiwari, V., Malik, S., and Wolfe, A. 1994. Power analysis of embedded software: a first step towards software power minimization. IEEE Transactions on VLSI Systems 2, 4 (Dec.), 437--445. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Tsuei, T.-F. and Vernon, M. K. 1992. A multiprocessor bus design model validated by system measurement. IEEE Transactions on Parallel and Distributed Systems 3, 6 (Nov.), 712--727. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Vijaykrishnan, N. et al. 2003. Evaluating integrated hardware-software optimizations using a unified energy estimation framework. IEEE Transactions on Computers 52, 1 (Jan.), 59--76. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Ziegenbein, D., Richter, K., Ernst, R., Thiele, L., and Teich, J. 2002. Spi---a system model for heterogeneously specified embedded systems. IEEE Transactions on VLSI Systems 10, 4 (Aug.), 379--389. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Power macromodeling of MPSoC message passing primitives

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in

        Full Access

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader
        About Cookies On This Site

        We use cookies to ensure that we give you the best experience on our website.

        Learn more

        Got it!