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Energy versus data integrity trade-offs in embedded high-density logic compatible dynamic memories

Published:09 March 2015Publication History

ABSTRACT

Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy trade-offs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.

References

  1. "ITRS - 2013 edition," 2013. {Online}. Available: http://www.itrs.netGoogle ScholarGoogle Scholar
  2. D. Somasekhar et al., "2 GHz 2 Mb 2T gain cell memory macro with 128 GBytes/sec bandwidth in a 65 nm logic process technology," JSSC, vol. 44, no. 1, pp. 174--185, 2009.Google ScholarGoogle Scholar
  3. K. Chun et al., "A 667 MHz logic-compatible embedded DRAM featuring an asymmetric 2T gain cell for high speed on-die caches," JSSC, 2012.Google ScholarGoogle Scholar
  4. Y. S. Park et al., "Low-power high-throughput LDPC decoder using non-refresh embedded DRAM," JSSC, vol. 49, no. 3, pp. 783--794, 2014.Google ScholarGoogle Scholar
  5. A. Teman et al., "Replica technique for adaptive refresh timing of gain-cell-embedded DRAM," IEEE TCAS-II: Express Briefs, vol. 61, no. 4, pp. 259--263, April 2014.Google ScholarGoogle ScholarCross RefCross Ref
  6. P. Gupta et al., "Underdesigned and opportunistic computing in presence of hardware variability," IEEE TCAD, vol. 32, no. 1, pp. 8--23, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. J. Henkel et al., "Multi-layer dependability: From microarchitecture to application level," in ACM-DAC '14, 2014, pp. 1--6. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. S. Venkataramani et al., "Quality programmable vector processors for approximate computing," in IEEE/ACM ISM 2013, 2013, pp. 1--12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. S. Liu et al., "Flikker: Saving DRAM refresh-power through critical data partitioning," SIGPLAN Not., vol. 46, no. 3, pp. 213--224, Mar. 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. A. Sampson et al., "Approximate storage in solid-state memories," in Proceedings IEEE/ACM ISM '13, 2013, pp. 25--36. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Y. Lee et al., "A 5.42nW/kB retention power logic-compatible embedded DRAM with 2T dual-VT gain cell for low power sensing applicaions," in Proc. IEEE A-SSCC, 2010.Google ScholarGoogle Scholar
  12. P. Meinerzhagen et al., "Impact of body biasing on the retention time of gain-cell memories," IET JoE, vol. 1, no. 1, 2013.Google ScholarGoogle Scholar
  13. L. Tran et al., "Heterogeneous memory management for 3D-DRAM and external DRAM with QoS," in ASP-DAC '13, 2013, pp. 663--668.Google ScholarGoogle Scholar
  14. R. Giterman et al., "4T gain-cell with internal-feedback for ultra-low retention power at scaled CMOS nodes," in Proc. IEEE ISCAS 2014.Google ScholarGoogle Scholar
  15. M. S. Khairy et al., "Algorithms and architectures of energy-efficient error-resilient MIMO detectors for memory-dominated wireless communication systems," IEEE TCAS-I, vol. 61-I, no. 7, 2014.Google ScholarGoogle Scholar
  16. H. Cho et al., "ERSA: error resilient system architecture for probabilistic applications," IEEE TCAD, vol. 31, no. 4, pp. 546--558, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. V. K. Chippa et al., "Analysis and characterization of inherent application resilience for approximate computing," in ACM-DAC '13, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. G. Karakonstantis et al., "On the exploitation of the inherent error resilience of wireless systems under unreliable silicon," in ACM-DAC '12, 2012, pp. 510--515. Google ScholarGoogle ScholarDigital LibraryDigital Library

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      • Published in

        cover image ACM Conferences
        DATE '15: Proceedings of the 2015 Design, Automation & Test in Europe Conference & Exhibition
        March 2015
        1827 pages
        ISBN:9783981537048

        Publisher

        EDA Consortium

        San Jose, CA, United States

        Publication History

        • Published: 9 March 2015

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        DATE '15 Paper Acceptance Rate206of915submissions,23%Overall Acceptance Rate518of1,794submissions,29%

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