Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Resilience and yield of flip-flops in future CMOS technologies under process variations and aging

In this study, the failure rate of flip-flops in future 16 nm complementary metal-oxide-semiconductor (CMOS) technologies is investigated. Using transistor level Monte Carlo simulations, the authors studied the influence of process variations and long term aging on the yield. The statistical distribution of the switching time (clock-to-Q delay) is shown to be highly asymmetric compared to a Gaussian distribution leading to a drastically enhanced fraction of very slow or metastable samples. Moreover, the failure rates will rise additionally during the device lifetime because of aging effects. To improve the yield the authors investigated several possible countermeasures including enhanced supply voltage or ensuring larger data-to-clock times as well as process and circuit optimisation.

References

    1. 1)
      • 5. Eireiner, M., Henzler, S., Georgakos, G., Berthold, J., Schmitt-Landsiedel, D.: ‘In-situ delay characterization and local supply voltage adjustment for compensation of local parametric variations’, IEEE J. Solid-State Circuits, 2007, 42, pp. 15831592 (doi: 10.1109/JSSC.2007.896695).
    2. 2)
      • 8. Wirnshofer, M., Heiss, L., Georgakos, G., Schmitt-Landsiedel, D.: ‘An energy-efficient supply voltage scheme using in-situ pre-error detection for on-the-fly voltage adaptation to PVT variations’. Proc. 13th Int. Symp. on Integrated Circuits (ISIC), 2011, pp. 9497.
    3. 3)
      • 20. Alioto, M., Consoli, E., Palumbo, G.: ‘Analysis and comparison in the energy-delay-area domain of nanometer CMOS flip-flops: part II – results and figures of merit’, IEEE Trans. VLSI Syst., 2011, 19/5, pp. 737750 (doi: 10.1109/TVLSI.2010.2041377).
    4. 4)
      • 13. Hassan, F., Vanderbauwhede, W., Rodríguez-Salazar, F.: ‘Impact of random dopant fluctuations on the timing characteristics of flip-flops’, IEEE Trans. VLSI Syst., 2012, 20/1, pp. 157161 (doi: 10.1109/TVLSI.2010.2088409).
    5. 5)
      • 7. Wang, J., Calhoun, B.H.: ‘Minimum supply voltage and yield estimation for large SRAMs under parametric variations’, IEEE Trans. VLSI Syst., 2011, 19/11, pp. 21202125 (doi: 10.1109/TVLSI.2010.2071890).
    6. 6)
      • 22. Consoli, E., Palumbo, G., Pennisi, M.: ‘Reconsidering high-speed design criteria for transmission-gate-based master–slave flip-flops’, IEEE Trans. VLSI Syst., 2012, 20/2, pp. 284295 (doi: 10.1109/TVLSI.2010.2098426).
    7. 7)
      • 2. Nassif, S.R., Mehta, N., Cao, Y.: ‘A resilience roadmap’. Proc. of DATE Conf., 2010, pp. 10111016.
    8. 8)
      • 4. Drapatz, S., Hofmann, K., Georgakos, G., Schmitt-Landsiedel, D.: ‘Impact of fast-recovering NBTI degradation on stability of large-scale SRAM arrays’. Proc. of ESSCIRC 2010, pp. 146149.
    9. 9)
      • 16. Rao, V.G., Mahmoodi, H.: ‘Analysis of reliability of flip-flops under transistor aging effects in nano-scale CMOS technology’. ICCD Conf. 2011, pp. 439440.
    10. 10)
      • 9. Moon, J., Aktan, M., Oklobdzija, V.: ‘Clocked storage elements robust to process variations’ (ASICON, 2009), pp. 827831.
    11. 11)
      • 19. Alioto, M., Consoli, E., Palumbo, G.: ‘Analysis and comparison in the energy-delay-area domain of nanometer CMOS flip-flops: part I methodology and design strategies’, IEEE Trans. VLSI Syst., 2030, 19/5, pp. 725736.
    12. 12)
      • 18. Predictive Technology Models, Arizona State University Nanoscale Group; available at: http://www.eas.asu.edu/~ptm/.
    13. 13)
      • 28. Rahman, A., Agostinelli, M., Bai, P., et al: ‘Reliability studies of a 32 nm system-on-chip (SoC) platform technology with 2nd generation high-K/metal gate transistors’ (IRPS, 2011), pp. 5D.3.15D.3.6.
    14. 14)
      • 27. Reisinger, H., Grasser, T., Ermisch, U., et al: ‘Understanding and modeling AC BTI’ (IRPS, 2011), pp. 597604.
    15. 15)
      • 24. Li, D., Chuang, P., Sachdev, M.: ‘Comparative analysis and study of metastability on high-performance flip-flops’ (ISQED, 2010), pp. 853860.
    16. 16)
      • 26. Wang, X., Brown, A., Cheng, B., Asenov, A.: ‘Statistical variability and reliability in nanoscale FinFETs’. Proc. of IEDM, 2011, pp. 103106.
    17. 17)
      • 31. Yilmaz, C., Heiß, L., Werner, C., Schmitt-Landsiedel, D.: ‘Modeling of NBTI-recovery effects in analog CMOS circuits’. Int. Reliability Physics Symp. IRPS 2013, paper 2A-4. Details of the model were also presented at the Synopsys User Group 2012 in Germany (http://www.synopsys.com/news/pubs/snug/2012/germany/A4_Werner_paper.pdf).
    18. 18)
      • 25. Synopsys Circuit Simulator: available at: http://www.synopsys.com/Tools/Verification/AMSVerification/CircuitSimulation/HSPICE.
    19. 19)
      • 23. Consoli, E., Alioto, M., Palumbo, G., Rabaey, J.: ‘Conditional push-pull pulsed latches with 726fJ·ps energy-delay product in 65 nm CMOS’ (ISSCC, 2012), pp. 482484.
    20. 20)
      • 1. Kuhn, K.J., Giles, M.D., Becher, D., et al: ‘Process technology variation’, IEEE Trans. Electron Devices, 2011, 58/8, pp. 21972208 (doi: 10.1109/TED.2011.2121913).
    21. 21)
      • 10. Stojanovic, V., Oklobdzija, V.G.: ‘Comparative analysis of master–slave latches and flip-flops for high-performance and low-power systems’, IEEE J. Solid-State Circuits, 1999, 34, pp. 536548 (doi: 10.1109/4.753687).
    22. 22)
      • 21. Alioto, M., Consoli, E., Palumbo, G.: ‘General strategies to design nanometer flip-flops in the energy-delay space’, IEEE Trans. Circuits Syst., 2010, 57/7, pp. 15831596 (doi: 0.1109/TCSI.2009.2033538).
    23. 23)
      • 11. I.T.R.S. for Semiconductors, ‘Edition 2007’. ITRS, Technical Report, 2007. Available at: http://www.itrs.net.
    24. 24)
      • 15. Sunagawa, H., Onodera, H.: ‘Variation-tolerant design of D-flip-flops’. SOC Conf. (SOCC), 2010, pp. 147151.
    25. 25)
      • 14. Lanuzza, M., De Rose, R., Frustaci, F., Perri, S., Corsonello, P.: ‘Impact of process variations on flip-flops energy and timing characteristics’. IEEE VLSI Symp., 2010, pp. 458460.
    26. 26)
      • 17. Hsu, S., Agarwal, A., Anders, M., et al: ‘A 280 mV-to-1.1 V 256b reconfigurable SIMD vector permutation engine with 2-dimensional shuffle in 22 nm CMOS’. ISSCC 2012, pp. 178180.
    27. 27)
      • 6. Wang, X., Roy, G., Saxod, O., Bajolet, A., Juge, A., Asenov, A.: ‘Simulation study of dominant statistical variability sources in 32-nm high-κ/metal gate CMOS’, IEEE Electron Device Lett., 2012, 33/5, pp. 643645 (doi: 10.1109/LED.2012.2188268).
    28. 28)
      • 29. Chen, X., Sanavedam, S., Narayanan, V., et al: ‘A cost effective 32 nm high-K/ metal gate CMOS technology for low power applications with single-metal/gate-first process’. VLSI Symp., 2008, pp. 8889.
    29. 29)
      • 12. Wang, X., Roy, S., Brown, A.R., Asenov, A.: ‘Impact of STI on statistical variability and reliability of decananometer MOSFETs’, IEEE Electron Device Lett., 2011, 32, pp. 479481 (doi: 10.1109/LED.2011.2108256).
    30. 30)
      • 30. Wirth, G.I., da Silva, R., Kaczer, B.: ‘Statistical model for MOSFET bias temperature instability component due to charge trapping’, IEEE Trans. Electron Devices, 2011, 58/8, pp. 27432751 (doi: 10.1109/TED.2011.2157828).
    31. 31)
      • 3. Nassif, S., Leeberger, V.K., Schlichtmann, U.: ‘Goldilocks Failures: not too soft, not too hard’ (IRPS, 2012), paper 2F1.1.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cds.2013.0122
Loading

Related content

content/journals/10.1049/iet-cds.2013.0122
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address