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Published in:
2013 | OriginalPaper | Chapter
Hardware Architecture for the Parallel Generation of Long-Period Random Numbers Using MT Method
Authors : Shengfei Wu, Jiang Jiang, Yuzhuo Fu
Published in: Computer Engineering and Technology
Publisher: Springer Berlin Heidelberg
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Random numbers are extremely important to the scientific and computational applications. Mersenne Twist(MT) is one of the most widely used high-quality pseudo-random number generators(PRNG) based on binary linear recurrences. In this paper, a hardware architecture for the generation of parallel long-period random numbers using MT19937 method was proposed. Our design is implemented on a Xilinx XC6VLX240T FPGA device and is capable of producing multiple samples each period. This performance let us obtain higher throughput than the non-parallelization architecture and software. The samples generated by our design are applied to a Monte Carlo simulation for estimating the value of
π
, and we achieve the accuracy of 99.99%.