What are the random number data rates for those applications?

One of the good features of ChaCha is that it is fast. A modern CPU can churn out Gbps of data. And in HW you can do it at low clock frequencies. This is the reason we use ChaCha as the CSPRNG in the Cryptech HSM.

> Just as you wouldn't want to use a general purpose PRNG for security applications so too you wouldn't want to use a secure PRNG for general purposes, particularly demanding applications such as Monte Carlo simulations.

Why not? It's perfectly valid to use a secure RNG for non-secure purposes.

As I mentioned, I've used ChaCha20 for those sort of purposes too. And the random number generation barely shows up as a fraction of the runtime.

i.e. improving 1% of the runtime by 99% isn't worth the overhead of having more than one random number generator.

The reason why is crypto RNG are much slower than something less secure. It really depends on the application, but in the code I wrote today a significant fraction of my application’s time was spent in the RNG function. By replacing the RNG I managed to speed up my code by a bit over 2 fold. I am not doing crypto work so this is great.

ChaCha is fast. very fast. see just below: https://news.ycombinator.com/item?id=9890599 I'm not sure why they marked it as "fairly slow" in the table in the OP.

Fast and slow are all relative - ChaCha is relatively fast but PGC is faster.

> Why not? It's perfectly valid to use a secure RNG for non-secure purposes.

It's much slower. Yes, in your application it was a fraction, but they are still much slower than non-secure RNG's.

One of the benefits of a PRNG is reproducibility. If you are doing a monte carlo simulation, then you can get good results while still starting runs from predictable seeds. (e.g. [0,1,2,3,4,...])

This gives you both good quality random numbers during the simulation run yet lets others reproduce your results and expand with more results if required.

ChaCha20 is a cipher, of course, it creates reproducible sequences.