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Energy-Aware Modeling of Scaled Heterogeneous Systems

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Abstract

Many-core processors are accelerating the performance of contemporary high-performance systems. Managing power consumption within these systems demands low-power architectures to increase power savings. One of the promising solutions offered today by microprocessor architects is asymmetric microprocessors that integrate different core architectures on a single die. This paper presents analytical models based on scaled power metrics to analyze the impact of various architectural design choices on scaled performance and power savings. The power consumption implications of different processing schemes and various chip configurations were also analyzed. Analysis shows that by choosing the optimal chip configuration, energy efficiency and energy savings can be increased considerably.

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References

  1. Moore, G.: Cramming more components onto integrated circuits. Electronics 38(8), 114–117 (1965)

  2. Woo, D.H., Lee, H.S.: Extending Amdahl’s law for energy-efficient computing in the many-core era. IEEE Comput. 38(11), 32–38 (2005)

    Article  Google Scholar 

  3. Kumar, R., et al.: Heterogeneous chip multiprocessors. IEEE Comput. 38(11), 32–38 (2005)

    Article  Google Scholar 

  4. Mantor, M.: Entering the golden age of heterogeneous computing. C-DAC PEEP2008. http://ati.amd.com/technology/streamcomputing/IUCAA_Pune_PEEP_2008

  5. Kogge, P., et al.: Exascale Computing Study: Technology Challenges in Achieving Exascale Systems. DARPA, Washington (2008)

    Google Scholar 

  6. Fuller, S.H., Millett, L.I.: Computing performance: game over or next level? IEEE Comput. 44(1), 31–38 (2011)

    Article  Google Scholar 

  7. Borkar, S.: Thousand Core Chips: A Technology Perspective. In: Proceedings of 44th Design Automation Conference (DAC 07), ACM Press, pp. 746–749 (2007)

  8. Marowka, A.: Back to thin-core massively parallel processors. IEEE Comput. 44(12), 49–54 (2011)

    Article  Google Scholar 

  9. Krishnamurthy, R.K., Kaul, H.: Ultra-low voltage technologies for energy-efficient special-purpose hardware accelerators. Intel Technol. J. 13(4), 100–117 (2009)

    Google Scholar 

  10. Hillis, D.: The Pattern on the Stone: The Simple Ideas that Make Computers Work. Basic Books, New York (1998)

    Google Scholar 

  11. Shi, Y.: Reevaluating Amdahl’s law and Gustafson’s law. http://www.cis.temple.edu/shi/docs/amdahl/amdahl.html (1996)

  12. Amdahl, G.M.: Validity of the Single-Processor Approach to Achieving Large-Scale Computing Capabilities. In: Proceedings of American Federation of Information Processing Societies, AFIPS Press, pp. 483–485 (1967)

  13. Gustafson, J.L.: Reevaluating Amdahl’s Law. Communications of the ACM, pp. 532–533 (1988)

  14. Gustafson, J.L.: The consequences of fixed time performance measurement. Proceedings of the Twenty-Fifth Hawaii International Conference on System Sciences, vol. 2, pp. 113–124 (1992)

  15. Marowka, A.: Analytical modeling of energy efficiency in heterogeneous processors. Comput. Electr. Eng. J. 39(8), 2566–2578 (2013)

    Article  Google Scholar 

  16. Marowka, A.: Extending Amdahl’s law for heterogeneous computing. In: Proceeding of the 2012 10th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA-2012), pp. 309–316

  17. Marowka, A.: Modeling the effects of DFS on power consumption in hybrid chip multiprocessors. In: Proceeding of 1st International Workshop on Energy Efficient SuperComputing (E2SC) Held in Conjunction with SC’13, Denver, Colorado, USA, November, 17–22, 2013, ACM digital library

  18. Hill, M.D., Marty, M.R.: Amdahl’s law in the multicore era. IEEE Comput. 41(7), 33–38 (2008)

  19. Sun, X.H., Chen, Y.: Reevaluating Amdahl’s law in the multicore era. J. Parallel Distrib. Comput. 70, 183–188 (2010)

    Article  MATH  Google Scholar 

  20. Esmaeilzadeh, H., Blem, E., St. Amant, R., Sankaralingam, K., Burger, D.C.: Dark silicon and the end of multicore scaling. In: Proceeding of 38th International Symposium on Computer Architecture (ISCA), pp. 365–376 (2011)

  21. Cho, S., Melhem, R.G.: Corollaries to Amdahl’s law for energy. IEEE Comput. Archit. Lett. 7(1), 25–28 (2008)

    Article  Google Scholar 

  22. Cho, S., Melhem, R.G.: On the interplay of parallelization, program performance, and energy consumption. IEEE Trans. Parallel Distrib. Syst. 21(3), 342–353 (2010)

    Article  Google Scholar 

  23. Hong, S., Kim, H.: An integrated GPU power and performance model. In: Proceeding of ISCA10, ACM, pp. 19–23 (2010)

  24. Pei, S., Zhang, J., Xiong, N., Kim M.-S., Gaudiot J.-L.: Performance-energy efficiency model of heterogeneous parallel multicore system. In: Green and Sustainable Computing Conference (IGSC), pp. 1–6 (2015)

  25. Karanikolaou, E.M., Milovanovic, E.I., Milovanovic, I.Z., Bekakos, M.P.: Performance scalability and energy consumption on distributed and many-core platforms. J. Supercomput. 70(1), 349–364 (2014)

    Article  Google Scholar 

  26. Kim, S.H., Kim, D., Lee, C., Jeong, W.S., Ro, W.W., Gaudiot, J.L.: A performance-energy model to evaluate single thread execution acceleration. Comput. Archit. Lett. 14(99), 1–4 (2014)

    Google Scholar 

  27. Lee, V.W. et al.: Debunking the 100X GPU vs. CPU myth: an evaluation of throughput computing on CPU and GPU. In ISCA’10 Proceedings of the 37th Annual International Symposium on Computer Architecture (2010)

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  1. Parallel Research Lab, Tel Aviv, Israel

    Ami Marowka

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  1. Ami Marowka
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Correspondence to Ami Marowka.

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Marowka, A. Energy-Aware Modeling of Scaled Heterogeneous Systems. Int J Parallel Prog 45, 1026–1045 (2017). https://doi.org/10.1007/s10766-016-0453-2

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  • DOI: https://doi.org/10.1007/s10766-016-0453-2

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