• DocumentCode
    2096784
  • Title

    Ultra fast neural models for analysis of electro/optical interconnects

  • Author

    Zhang, Q.J. ; Wilson, G. ; Venkatachalam, R. ; Sarangan, A. ; Williamson, J. ; Wang, F.

  • fYear
    1997
  • fDate
    18-21 May 1997
  • Firstpage
    1134
  • Lastpage
    1137
  • Abstract
    The key to realize low-cost, low-power and high-frequency systems with shrinking design margins and expanding system complexities lies in the effective use of design automation tools in both architectural and detailed design stages. The need to reduce design iterations of such systems further demands that the tools be fast and reliable. A new modeling paradigm is presented to drastically speedup model evaluation and simulation of electrical and optical interconnects. Transmission line models are developed based on neural networks for signal integrity evaluation, allowing massive analysis of delay, crosstalk and switching noise on large numbers of signal tracks to be performed in a timely fashion. Neural models for laser diodes is also developed for analysis of optical systems. Such analysis can be used during architectural and detailed physical design stages to catch potential design errors early and more accurately, contributing to increased design efficiency
  • Keywords
    integrated circuit interconnections; neural nets; optical interconnections; semiconductor lasers; transmission line theory; crosstalk; delay; design automation; electrical interconnect; laser diode; optical interconnect; signal integrity; simulation; switching noise; transmission line; ultrafast neural network model; Design automation; Diode lasers; Neural networks; Optical crosstalk; Optical interconnections; Optical noise; Performance analysis; Performance evaluation; Signal analysis; Transmission lines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Components and Technology Conference, 1997. Proceedings., 47th
  • Conference_Location
    San Jose, CA
  • ISSN
    0569-5503
  • Print_ISBN
    0-7803-3857-X
  • Type

    conf

  • DOI
    10.1109/ECTC.1997.606317
  • Filename
    606317