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
Link To Document :
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