  The Graphcore Intelligence Processing Unit contains an original pseudorandom
number generator (PRNG) called xoroshiro128aox, based on the F2-linear
generator xoroshiro128. It is designed to be cheap to implement in hardware and
provide high-quality statistical randomness. In this paper, we present a
rigorous assessment of the generator's quality using standard statistical test
suites and compare the results with the fast contemporary PRNGs xoroshiro128+,
pcg64 and philox4x32-10. We show that xoroshiro128aox mitigates the known
weakness in the lower order bits of xoroshiro128+ with a new 'AOX' output
function by passing the BigCrush and PractRand suites, but we note that the
function has some minor non uniformities. We focus our testing with specific
tests for linear artefacts to highlight the weaknesses of both xoroshiro128
PRNGs, but conclude that they are hard to detect, and xoroshiro128aox otherwise
provides a good trade off between statistical quality and hardware
implementation cost.
