On Nov 4, 2008, at 12:11 AM, Josiah Carlson wrote:
There is no shortage of algorithms (such as matrix multiplication)
that are parallelizable but not particularly good candidates for an
IPC-based multiprocessing paradigm.
Ahh, but those algorithms aren't going to be written in Python; they
are going to be written in C, and are going to manipulate memory
directly. With such things, you can use standard Python threads,
call into your C runtime, and release the GIL. Alternatively, you
can use the mmap module to store your data, shared across multiple
processes, using the same direct-memory access as you would with
multiple threads and GIL release.
That's the thing, right now you can't even use python to sketch one of
those algorithms and for example compare performance with a non
parallel version.
Also with four cores on common intel processor you might be happy with
your algo being 4x faster while being quite easy to develop (not
needing to use c).
I personally think this will be too much work on
--
Leonardo Santagada
santagada at gmail.com
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