• DocumentCode
    1369155
  • Title

    Yield-Driven Near-Threshold SRAM Design

  • Author

    Chen, Gregory ; Sylvester, Dennis ; Blaauw, David ; Mudge, Trevor

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA
  • Volume
    18
  • Issue
    11
  • fYear
    2010
  • Firstpage
    1590
  • Lastpage
    1598
  • Abstract
    Voltage scaling is desirable in static RAM (SRAM) to reduce energy consumption. However, commercial SRAM is susceptible to functional failures when VDD is scaled down. Although several published SRAM designs scale VDD to 200-300 mV, these designs do not sufficiently consider SRAM robustness, limiting them to small arrays because of yield constraints, and may not correctly target the minimum energy operation point. We examine the effects on area and energy for the differential 6T and 8T bit cells as VDD is scaled down, and the bit cells are either sized and doped, or assisted appropriately to maintain the same yield as with full VDD. SRAM robustness is calculated using importance sampling, resulting in a seven-order run-time improvement over Monte Carlo sampling. Scaling 6T and 8T SRAM VDD down to 500 mV and scaling 8T SRAM to 300 mV results in a 50% and 83% dynamic energy reduction, respectively, with no reduction in robustness and low area overhead, but increased leakage per bit. Using this information, we calculate the supply voltage for a minimum total energy operation (VMIN) based on activity factor and find that it is significantly higher for SRAM than for logic.
  • Keywords
    SRAM chips; VLSI; circuit stability; importance sampling; integrated circuit design; low-power electronics; 6T bit cell; 8T bit cell; SRAM robustness; VLSI; activity factor; assist circuits; doped bit cells; dynamic energy reduction; energy consumption reduction; importance sampling; leakage; minimum total energy operation; sized bit cells; static RAM; supply voltage; voltage scaling; yield-driven near-threshold SRAM design; Circuits; Delay; Dynamic voltage scaling; Energy consumption; Monte Carlo methods; Noise reduction; Noise robustness; Random access memory; Read-write memory; Resource description framework; Low power; near threshold; robustness; static RAM (SRAM); threshold voltage tuning;
  • fLanguage
    English
  • Journal_Title
    Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-8210
  • Type

    jour

  • DOI
    10.1109/TVLSI.2009.2025766
  • Filename
    5238569