Efficient Hardware Generation of Random Variates with Arbitrary Distributions

Authors:
David B. Thomas;Wayne Luk
Affiliations:
Imperial College London;Imperial College London
Venue:
FCCM '06 Proceedings of the 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Year:
2006

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Abstract

This paper presents a technique for efficiently generating random numbers from a given probability distribution. This is achieved by using a generic hardware architecture, which transforms uniform random numbers according to a distribution mapping stored in RAM, and a software approximation generator that creates distribution mappings for any given target distribution. This technique has many features not found in current non-uniform random number generators, such as the ability to adjust the target distribution while the generator is running, per-cycle switching between distributions, and the ability to generate distributions with discontinuities in the Probability Density Function.