AFAIK, CMRG (MRG31k3p) is more equidistributed than Mersenne Twister, but the period is much shorter. However, MT is getting acceptance as the PRNG of choice for numerical work. And when we are doing stochastic simulations in Python, the speed of the PRNG is unlikely to be the bottleneck.
Sturla Frédéric Bastien <no...@nouiz.org> wrote: > Hi, > > In a ticket I did a coment and Charles suggested that I post it here: > > In Theano we have an C implementation of a faster RNG: MRG31k3p. It is > faster on CPU, and we have a GPU implementation. It would be > relatively easy to parallize on the CPU with OpenMP. > > If someone is interested to port this to numpy, their wouldn't be any > dependency problem. No license problem as Theano license have the same > license as NumPy. > > The speed difference is significant, but I don't recall numbers. > > Fred _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
