Re: parallel random numbers generator

OK, let me try to be somewhat more specific: Particular needs for this
simulation are alike, I guess, to needs of most of MC based
simulations to be implemented on CUDA, which means the demands from
RNG are: to generate many large sequences of random numbers in
parallel, to have these sequences manifesting low correlation between
each other and being generally "good" in other statistical regards,
then to have small state (Mersenne Twister need 624 numbers of state,
this is way too big) in order to be able to keep it in CUDA shared
memory (otherwise the performance will suffer heavily). Seems like
good choice may be to use some of RNGs with small state for each
thread of execution, but initialized with different seeds (generated
by another RNG). But again - there are way too much options available
for both "main" and "seeding" RNG, so the question is: which ones to
choose, and how to measure the quality of the results?
.

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