> In the scientific world, MPI is the standard API of choice for doing > parallel processing, so if we're after standards, supporting MPI > would seem to be more attractive than the processing module. > > http://pypi.python.org/pypi/mpi4py
Of course, for MPI, pyprocessing's main functionality (starting new activities) isn't needed - you use the vendor's mpirun binary, which will create as many processes as you wish, following a policy that was set up by the cluster administration, or that you chose in a product-specific manner (e.g. what nodes to involve in the job). If my task was high-performance computing, I would indeed use MPI and ignore pyprocessing. > In the enterprise world, you often find CORBA based solutions. > > http://omniorb.sourceforge.net/ Same here: I would prefer CORBA of pyprocessing when I want a componentized, distributed application. > And then, of course, you have a gazillion specialized solutions > such as PyRO: > > http://pyro.sourceforge.net/ I personally would not use that library, although I know others are very fond of it. Regards, Martin _______________________________________________ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
