• DocumentCode
    2705429
  • Title

    Applying GPU and POSIX thread technologies in massive remote sensing image data processing

  • Author

    Liu, Yuehu ; Chen, Bin ; Yu, Hao ; Zhao, Yong ; Huang, Zhou ; Fang, Yu

  • Author_Institution
    Inst. of Remote Sensing & Geographic Inf. Syst., Peking Univ., Beijing, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Since the introduction of CUDA (Compute Unified Device Architecture), GPU (Graphics Processing Unit) was used in various fields rapidly. Some researchers used the GPU computing technology in remote sensing image processing, and revealed that one hundred times speedup could be obtained. Current GPU-based approaches need to load all the image data at a time prior to image processing. However, the current computer memory and GPU memory are limited, and are not big enough for loading the remote sensing image data which are always massive. Hence, current GPU-based image processing approaches cannot be directly applied in remote sensing image processing. Under this situation, this paper proposes a dual-parallel processing mechanism, which is based on GPU and POSIX thread technologies, in massive remote sensing image data processing. Experimental results illustrate that our methodology can not only deal with massive remote sensing image data, but also improve the processing efficiency greatly.
  • Keywords
    application program interfaces; computer graphic equipment; coprocessors; image processing; parallel processing; remote sensing; CUDA; GPU; POSIX; compute unified device architecture; dual-parallel processing mechanism; graphics processing unit; massive remote sensing image data processing; Computer architecture; Data processing; Graphics processing unit; Image processing; Instruction sets; Parallel processing; Remote sensing; CUDA; GPU; POSIX thread; RS; image processing; massive;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2011 19th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-61284-849-5
  • Type

    conf

  • DOI
    10.1109/GeoInformatics.2011.5980671
  • Filename
    5980671