• DocumentCode
    2482537
  • Title

    Accelerating leukocyte tracking using CUDA: A case study in leveraging manycore coprocessors

  • Author

    Boyer, Michael ; Tarjan, David ; Acton, Scott T. ; Skadro, Kevin

  • Author_Institution
    Depts. of Comput. Sci., Univ. of Virginia, Charlottesville, VA, USA
  • fYear
    2009
  • fDate
    23-29 May 2009
  • Firstpage
    1
  • Lastpage
    12
  • Abstract
    The availability of easily programmable manycore CPUs and GPUs has motivated investigations into how to best exploit their tremendous computational power for scientific computing. Here we demonstrate how a systems biology application - detection and tracking of white blood cells in video microscopy - can be accelerated by 200times using a CUDA-capable GPU. Because the algorithms and implementation challenges are common to a wide range of applications, we discuss general techniques that allow programmers to make efficient use of a manycore GPU.
  • Keywords
    biology computing; blood; cellular biophysics; computer graphic equipment; coprocessors; medical image processing; microscopy; object detection; CUDA-capable GPU; leukocyte tracking; manycore coprocessors; programmable manycore CPUs; programmable manycore GPUs; scientific computing; systems biology application; video microscopy; white blood cell detection; white blood cell tracking; Acceleration; Application software; Biology computing; Computer architecture; Concurrent computing; Coprocessors; Iterative algorithms; Programming profession; Systems biology; White blood cells;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on
  • Conference_Location
    Rome
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4244-3751-1
  • Electronic_ISBN
    1530-2075
  • Type

    conf

  • DOI
    10.1109/IPDPS.2009.5160984
  • Filename
    5160984