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The output of a CS_P_RNG is by definition reproducible. And there’s really only a small number of applications where, say, ChaCha8 would be too slow.



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

Chacha8 has a throughput of 2GB/s and xoshiro256++ has a throughput of 8GB/s

For Monte-Carlo, the RNG is definitely the bottleneck. For load balancing of short tasks the RNG is the bottleneck.


On my thermally-limited laptop, aes-128-ctr runs at over 9 GB/s. If pure speed is the goal, then AES-NI is faster than the fastest PRNG. Seek to a deterministic point by advancing the counter. Choose random seed with a fresh key. What more could you want? ("portable speed!")

You can eek out another 10% or so if you dial it back to the recommendations of the "too much crypto" paper: 9x AES rounds (versus 10).

https://eprint.iacr.org/2019/1492




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