• DocumentCode
    2135314
  • Title

    A new hardware architecture for sampling the exponential distribution

  • Author

    Bachir, Tarek Ould ; Sawan, Mohamad ; Brault, Jean-Jules

  • Author_Institution
    Dept. of Electr. Eng. Montreal, Ecole Polytech. de Montreal, Montreal, QC, Canada
  • fYear
    2008
  • fDate
    4-7 May 2008
  • Abstract
    Hardware acceleration in high performance computing context is of growing interest, particularly in the field of Monte Carlo methods where the resort to FPGA technology enhances execution speed by several orders. For this purpose, a particular attention has been given lately to hardware-based non-uniform random variate generators. In this paper we present both a hardware-dedicated decision tree technique for the generation of exponential variates and a derived architecture implemented in FPGA. The proposed design passes the chi2 test with a p-value of 0.5499 and ensures absence of serial correlation. The exponential random number generator reaches 375 MHz on a Xilinx Virtex II Pro FPGA and occupies about 3 % of the available space.
  • Keywords
    Monte Carlo methods; decision trees; exponential distribution; field programmable gate arrays; logic design; sampling methods; FPGA technology; Monte Carlo method; exponential distribution sampling; exponential random number generator; hardware architecture; hardware-dedicated decision tree technique; Acceleration; Computer architecture; Decision trees; Exponential distribution; Field programmable gate arrays; Hardware; High performance computing; Random number generation; Sampling methods; Testing; Sampling methods; exponential distribution; random number generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on
  • Conference_Location
    Niagara Falls, ON
  • ISSN
    0840-7789
  • Print_ISBN
    978-1-4244-1642-4
  • Electronic_ISBN
    0840-7789
  • Type

    conf

  • DOI
    10.1109/CCECE.2008.4564770
  • Filename
    4564770