numpy and Global Interpreter Lock

Embarrassingly parallel? Numpy? Sounds like a good candidate for PyCUDA or PyOpenCL.

You will probably find answers to all your questions regarding NumPy and parallel programming on the official wiki.

Also, have a look at this recipe page -- it contains example code on how to use NumPy with multiple threads.

Quite some numpy routines release GIL, so they can be efficiently parallel in threads (info). Maybe you don't need to do anything special!

You can use this question to find whether the routines you need are among the ones that release GIL. In short, search for ALLOW_THREADS or nogil in the source.

(Also note that MKL has the ability to use multiple threads for a routine, so that's another easy way to get parallelism, although possibly not the fastest kind).