I suppose it's that last part. I tried using some of the ipython parallel stuff, but found it to be pretty clumsy (although this was about 2y ago). Is there a better solution for parallelization in python?
I have never used the parallel stuff in ipython, but my understanding was that it was more for cluster-kind of stuff. This is getting significantly rewritten, also, so things are changing there.
But the way most people use parallel stuff in numpy is: first use BLAS/LAPACK which is multithreaded, then use multiprocessing, etc... It depends on what you are trying to achieve, but my understanding is that as soon as you use arrays and the liked, clojure is not that helpful compared to a much more primitive runtime as python, because all the parallel goodies of clojure are not available anymore. But I have never seriously used clojure, so I may be dead wrong.
Don't hesitate to ask on the ML (while I know numpy fairly well inside out, I am not the best person to talk about parallelism). There is also a lot of talks available in the scipy conferences video. See http://conference.scipy.org/scipy2010/schedule.html for 2010.
