On Dec 19, 3:16 pm, sturlamolden <sturlamol...@yahoo.no> wrote: > On 19 Des, 14:06, Carl Johan Rehn <car...@gmail.com> wrote: > > > Matlab and numpy have (by chance?) the exact names for the same > > functionality, > > Common ancenstry, NumPy and Matlab borrowed the name from IDL. > > LabView, Octave and SciLab uses the name randn as well. > > > So the basioc question is, how can I speed up random number > > generation? > > The obvious thing would be to compile ziggurat yourself, and turn on > optimization flags for your hardware.http://www.jstatsoft.org/v05/i08/ > > P.S. Be careful if you consider using more than one processor. > Multithreading is a very difficult issue with PRNGs, becuase it is > difficult to guarrantee they are truely independent. But you can use a > producer-consumer pattern, though: one thread constantly producing > random numbers (writing into a buffer or pipe) and another thread(s) > consuming them.
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? Carl Carl -- http://mail.python.org/mailman/listinfo/python-list
