• DocumentCode
    1180085
  • Title

    Mixed-Signal Approximate Computation: A Neural Predictor Case Study

  • Author

    Amant, Renée St ; Jimenez, D.A. ; Burger, Doug

  • Author_Institution
    Univ. of Texas at Austin, Austin, TX
  • Volume
    29
  • Issue
    1
  • fYear
    2009
  • Firstpage
    104
  • Lastpage
    115
  • Abstract
    As transistors shrink and processors trend toward low power, maintaining precise digital behavior grows more expensive. Replacing digital units with analog equivalents sometimes allows similar computation to be performed at higher speed using less power. As a case study in mixed-signal approximate computation, the authors describe an enhanced neural prediction algorithm and its efficient analog implementation.
  • Keywords
    approximation theory; mixed analogue-digital integrated circuits; analog equivalents; digital units; enhanced neural prediction algorithm; mixed-signal approximate computation; Accuracy; Algorithm design and analysis; Analog circuits; Analog computers; Circuit noise; Computer aided software engineering; High performance computing; History; Prediction algorithms; Wire; analog circuits; approximate computation; computer architecture; imprecise; low power; mixed signal; neural predictor; programmable;
  • fLanguage
    English
  • Journal_Title
    Micro, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1732
  • Type

    jour

  • DOI
    10.1109/MM.2009.10
  • Filename
    4796174