  This work considers the deployment of pseudo-random number generators (PRNGs)
on graphics processing units (GPUs), developing an approach based on the
xorgens generator to rapidly produce pseudo-random numbers of high statistical
quality. The chosen algorithm has configurable state size and period, making it
ideal for tuning to the GPU architecture. We present a comparison of both speed
and statistical quality with other common parallel, GPU-based PRNGs,
demonstrating favourable performance of the xorgens-based approach.
