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I am curious about why you think numpy/scipy does not fit that bill ? Python is a straightforward general purpose programming language, has a lot of stats funct
by cdavid 16y ago
I am curious about why you think numpy/scipy does not fit that bill ? Python is a straightforward general purpose programming language, has a lot of stats functionalities, can access GPU functions. While python's story for parallel programming is pretty poor, it is actually quite decent for numerical computation, because parallelizing those is not very difficult in general.
- phren0logy 16y agoI 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?
- cdavid 16y agoI 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.
- phren0logy 16y agoThanks, I'll try that approach.
- cdavid 16y agoDon'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 http://conference.scipy.org/scipy2010/schedule.html for 2010.