• DocumentCode
    159777
  • Title

    Approximate computing for efficient information processing

  • Author

    Venkataramani, Swagath ; Chakradhar, Srimat T. ; Roy, Kaushik ; Raghunathan, Anand

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
  • fYear
    2014
  • fDate
    16-17 Oct. 2014
  • Firstpage
    9
  • Lastpage
    10
  • Abstract
    The gap created due to diminishing benefits from technology scaling on the one hand, and projected growth in computing demand from future workloads on the other, leads to a need for new sources of computing efficiency. Fortunately, the workloads that are driving demand across the computing spectrum also present new opportunities. At the server end, the demand for computing is driven by the need to organize, analyze, interpret, and search through exploding digital data. In mobile devices and deeply embedded systems, the creation and consumption of richer media and the need to interact more naturally and intelligently with users and the environment are trends that drive much of the computing demand.
  • Keywords
    mobile computing; multimedia systems; approximate computing; computing demand; deeply embedded systems; information processing; media consumption; media creation; mobile devices; technology scaling; Algorithm design and analysis; Approximation algorithms; Approximation methods; Computer architecture; Hardware; Resilience; Software;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Embedded Systems for Real-time Multimedia (ESTIMedia), 2014 IEEE 12th Symposium on
  • Conference_Location
    Greater Noida
  • Type

    conf

  • DOI
    10.1109/ESTIMedia.2014.6962339
  • Filename
    6962339