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Abstract
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| In this work we present a very accurate floating point FPGA implementation of a Gaussian random number generator (GRNG) based on the inversion method. The inverse Gaussian cumulative distribution function (GCDF−1) is approximated using a quintic degree segment interpolation with Hermite coefficients and an accuracy-adaptative segmentation which divides the GCDF−1 into several non-uniform segments. Our architecture generates simple floating point samples of 32 bits with an accuracy of 20 bits of mantissa, achieving a 185 MHz speed and a troughput of one sample per cycle on a Xilinx Virtex-II FPGA. (Proceedings: pp. 871-874). | |
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International
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Si |
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Congress
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MWSCAS 2007 50st IEEE International Midwest Symposium on Circuits and Systems |
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960 |
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Place
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Montréal (Canada) |
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Reviewers
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Si |
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ISBN/ISSN
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978-1-4244-1175-7 |
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Start Date
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05/08/2007 |
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End Date
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08/08/2007 |
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