On Dec 19, 4:47 pm, sturlamolden <sturlamol...@yahoo.no> wrote: > On 19 Des, 16:20, Carl Johan Rehn <car...@gmail.com> wrote: > > > How about mulit-core or (perhaps more exciting) GPU and CUDA? I must > > admit that I am extremely interested in trying the CUDA-alternative. > > > Obviously, cuBLAS is not an option here, so what is the safest route > > for a novice parallel-programmer? > > The problem with PRNG is that they are iterative in nature, and > maintain global states. They are therefore very hard to vectorize. A > GPU will not help. The GPU has hundreds of computational cores that > can run kernels, but you only get to utilize one. > > Parallel PRNGs are an unsolved problem in computer science.
>>>How did you time it? Well, in Matlab I used "tic; for i = 1:1000, randn(100, 10000), end; toc" and in IPython i used a similar construct but with "time" instead of tic/(toc. >>> Parallel PRNGs are an unsolved problem in computer science. Thanks again for sharing your knowledge. I had no idea. This means that if I want to speed up my application I have to go for the fastest random generator and focus on other parts of my code that can be vectorized. Carl -- http://mail.python.org/mailman/listinfo/python-list
