Non-Uniform Random Number Generation Through Piecewise Linear Approximations

This paper presents a hardware architecture for non-uniform random number generation, which allows the generator´s distribution to be modified at run-time without reconfiguration. The architecture is based on a piecewise linear approximation, using just one table lookup, one comparison and one subtract operation to map from a uniform source to an arbitrary non-uniform distribution, resulting in very low area utilisation and high speeds. Customisation of the distribution is fully automatic, requiring less than a second of CPU time to approximate a new distribution, and around 1000 cycles to switch distributions at run-time. Comparison with Gaussian specific generators show that the new architecture uses less than half the resources, provides a higher sample rate, and retains statistical quality for up to 50 billion samples, but can also generate other distributions.