Random seeds and multithreading in numba
In parallel, each worker need to have its own seed as a random number generator cannot be both efficient and and thread safe at the same time. If you want the number of threads not to have an impact on the result, then you need to split the computation in chunks and set a seed for each chunk (computed by one thread). The seed chosen for a given chunk can be for example the chunk ID.
I wondered if there is any way to reproducibly draw random numbers when using parallel==True with jitted functions in numba. I know that for singlethreaded code, you can set the random seed for numpy or the standard random module within a jitted function, but that does not seem to work for multithreaded code. Maybe there is some sort of workaround one could use?