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.

翻译：石芯情报处理股以F2-线性发电机xoroshiro128128xx1的原假冒号码发电机(PRNG)为原型,以F2-线性发电机xoroslo128aox为基础,设计成本低廉,以硬件实施并提供高质量的统计随机性。在本文中,我们使用标准的统计测试套件对发电机的质量进行严格评估,并将结果与当代快速的PRNGsxoroshiro128+、pcg64和phox4x32-10进行比较。我们表明,xoroshiro128aox通过通过大粉丝和PractRand套件来降低128+x的较低顺序的已知弱点,而新的“AOX”输出功能,但我们注意到,该功能有一些细微的不统一之处。我们集中对线性工艺进行具体测试,以突出Xoroshiro128PRNGs的弱点,但结论是难以检测到的,而xoroshilo128ax则提供了统计质量和硬件执行成本之间的良好交易。