• DocumentCode
    3706131
  • Title

    A low-energy ASIP with flexible exponential Golomb codec for lossless data compression toward artificial vision systems

  • Author

    Tomoki Sugiura;Jaehoon Yu;Yoshinori Takeuchi;Masaharu Imai

  • Author_Institution
    Graduate School of Information Science and Technology, Osaka University, Suita, Osaka, Japan
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper proposes an application-domain specific instruction-set processor (ASIP) with dedicated instructions for lossless data compression and decompression process to be used in artificial vision systems. Proposed ASIP has dedicated instructions to accelerate the performance to codec operations of Exponential Golomb coding, where the coding parameter value can be set by the user in order to maximize the compression ratio. Experimental results through simulation show that the proposed ASIP reduces execution cycles by 88% for compression and 42% for decompression, and reduces energy consumption by 85% for compression and 40% for decompression, compared with the base reduced instruction set computer processor.
  • Keywords
    "Codecs","Encoding","Yttrium","Machine vision","Logic gates","Data compression","Energy consumption"
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE
  • Type

    conf

  • DOI
    10.1109/BioCAS.2015.7348302
  • Filename
    7348302