On Mon, Jun 23, 2008 at 2:53 PM, Brian Granger <[EMAIL PROTECTED]> wrote:
> > So in summary, I am going ahead right now and will come back and report > in a > > month or so. > > > Great! > > Cheers, > Thanks for your comments. I guess we have multiple parties involved : multiple users with differing needs, Python language designers and CPython developers, 3rd party tool like Cython which are widely used and the more experimental tools like unPython. People also have various backgrounds : people experienced with threads and locks, experienced with OpenMP, experienced with MPI, experienced with erlang and actors etc. Similarly, multiple projects like pyprocessing exist which provide libraries for process based parallelism. You can also use MPI as pointed out as another approach. Bindings to existing parallel C/C++ libraries are another way people currently utilize parallelism. For example numpy can use threaded BLAS and people have added python bindings to many distributed solvers. Stackless is another interesting programming model and it appears someone is working on a patch to enable real concurrency in stackless?? (If somebody knows about stackless, comments will be appreciated). You can use Java threads in Jython. (and same goes for IronPython and CLR??) I guess different problems will require different tools and as people gain more experience, they will get to know which model applies for which problem. Parallelism in Python is not an easy issue and given the various parties involved and their needs and viewpoints, it is best to have some experimental implementations which can be used as reference points later to have a more informed debate. thanks, rahul
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