• DocumentCode
    2764727
  • Title

    A Memory Centric Kernel Framework for Accelerating Short-Range, Interactive Particle Simulation

  • Author

    Stewart, Ian ; Zhou, Shujia

  • Author_Institution
    Univ. of Maryland Baltimore County, Baltimore, MD, USA
  • fYear
    2010
  • fDate
    17-20 May 2010
  • Firstpage
    802
  • Lastpage
    807
  • Abstract
    To maximize the performance of emerging multi- and many-core accelerators such as the IBM Cell B.E. and the NVIDIA GPU, a Memory Centric Kernel Framework (MCKF) was developed. MCKF allows a user to decompose the physical space of an application based on the available fast memory in the accelerators. In this way, reducing the communication cost in accessing data can maximize the extraordinary computing power of the accelerators. MCKF is both generic and flexible because it encapsulates hardware-specific characteristics. It has been implemented and tested for short-range inter-active particle simulation on IBM Cell B.E. blades.
  • Keywords
    computer graphic equipment; digital simulation; parallel algorithms; storage management; IBM cell BE blades; MCKF; NVIDIA GPU; memory centric kernel framework; short-range inter-active particle simulation; Acceleration; Clouds; Computational modeling; Costs; Engines; Grid computing; Kernel; Memory management; Particle accelerators; Physics computing; GPU; IBM Cell B.E.; accelerator; kernel; memory management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster, Cloud and Grid Computing (CCGrid), 2010 10th IEEE/ACM International Conference on
  • Conference_Location
    Melbourne, VIC
  • Print_ISBN
    978-1-4244-6987-1
  • Type

    conf

  • DOI
    10.1109/CCGRID.2010.108
  • Filename
    5493381