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I was curious. The rust rand library has implementations for a lot of rngs - prngs and csrngs. All with high quality implementations as far as I can tell.

They agree with your numbers: their fast, high quality prng implementations are about 8gb/sec and chacha is about 2gb/sec:

https://rust-random.github.io/book/guide-rngs.html

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There are ways to make much faster PRNGs; I designed one that reaches 53 GB/s[0] (0.06 cycles per byte) with better quality than those listed in the article.

But I agree with tczajka: good engineering practice ought to be to start with a CSPRNG. First make it work, then make it fast. With truly random data, you know your algorithm works, and can then check if there is a quality loss when switching away. The performance of CSPRNG is so optimized that it is seldom the bottleneck anyway.

[0]: https://github.com/espadrine/shishua#comparison

Cool! I wonder if the rand crate would be interested in adding this. I love all their sampling functions - shuffle, choose, uniform, etc. But it looks like shishua is way faster than any of their rngs.

This is a very informative repo and associated blog posts.

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