• DocumentCode
    3361868
  • Title

    A method using circuit/substrate macro modeling to analyze substrate noise in a 3.2-GHz 350M-transistor microprocessor

  • Author

    Sode, Mikiko ; Kajita, Mikihiro ; Nakayama, Naoya ; Nakamoto, Satoshi

  • Author_Institution
    NEC Electron. Corp., Kawasaki
  • fYear
    2008
  • fDate
    21-24 Sept. 2008
  • Firstpage
    687
  • Lastpage
    690
  • Abstract
    Substrate noise analysis has become increasingly important in recent LSI design. This is because substrate noise, which affects PLLs, causes jitter that results in timing error. Conventional analysis techniques of substrate noise are, however, impractical for large-scale designs that have hundreds of millions of transistors because the computational complexity is too huge. To solve this problem, we have developed a fast substrate noise analysis technique for large-scale designs, one in which a chip is divided into multiple domains by using current density variation and the circuits of each domain are reduced into a macro model. Using this technique, we have designed a microprocessor chip for use in the supercomputer SX-9 (die size: 20 mm times 21 mm, frequency: 3.2 GHz, transistor count: 350 M). Computation time with this design is five times shorter than [2] that with a 1/3000 scale design using a conventional technique, while resulting discrepancy with measured period jitter is less than 15%.
  • Keywords
    large scale integration; microprocessor chips; network synthesis; phase locked loops; transistor circuits; M-transistor microprocessor; PLL; circuit/substrate macro modeling; large scale integration design; microprocessor chip; substrate noise analysis; Circuit noise; Computational complexity; Current density; Error analysis; Large scale integration; Large-scale systems; Microprocessor chips; Noise reduction; Supercomputers; Timing jitter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Custom Integrated Circuits Conference, 2008. CICC 2008. IEEE
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    978-1-4244-2018-6
  • Electronic_ISBN
    978-1-4244-2019-3
  • Type

    conf

  • DOI
    10.1109/CICC.2008.4672179
  • Filename
    4672179