• DocumentCode
    1329797
  • Title

    A Bias-Dependent Model for the Impact of Process Variations on the SRAM Soft Error Immunity

  • Author

    Mostafa, Hassan ; Anis, M. ; Elmasry, M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada
  • Volume
    19
  • Issue
    11
  • fYear
    2011
  • Firstpage
    2130
  • Lastpage
    2134
  • Abstract
    Nanometer SRAM cells are more susceptible to the particle strike soft errors and the increased statistical process variations, in advanced nanometer CMOS technologies. In this paper, an analytical model for the critical charge variations accounting for both die-to-die (D2D) and within-die (WID) variations, over a wide range of bias conditions, is proposed. The derived model is verified and compared to Monte Carlo simulations by using industrial hardware-calibrated 65-nm CMOS technology. This paper shows the impact of the coupling capacitor, one of the most common soft error mitigation techniques, on the critical charge variability. It demonstrates that the adoption of the coupling capacitor reduces the critical charge variability. The derived analytical model accounts for the impact of the supply voltage, from 0.1 to 1.2 V, on the critical charge and its variability.
  • Keywords
    CMOS memory circuits; SRAM chips; capacitors; nanoelectronics; SRAM soft error immunity; bias-dependent model; coupling capacitor; critical charge variation; die-to-die variation; nanometer CMOS technology; nanometer SRAM cell; size 65 nm; soft error mitigation technique; static random access memory; statistical process variation; within-die variation; Analytical models; Mathematical model; Monte Carlo methods; Random access memory; Semiconductor device modeling; Threshold voltage; Transistors; Deep sub-micrometer; process variations; reliability; soft errors; static random access memory (SRAM);
  • fLanguage
    English
  • Journal_Title
    Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-8210
  • Type

    jour

  • DOI
    10.1109/TVLSI.2010.2068317
  • Filename
    5580133