>>> As far as I can tell, it seems >>> CPython's current state can't CPU bound parallelization in the same >>> address space. >> That's not true. >> > > Um... So let's say you have a opaque object ref from the OS that > represents hundreds of megs of data (e.g. memory-resident video). How > do you get that back to the parent process without serialization and > IPC?
What parent process? I thought you were talking about multi-threading? > What should really happen is just use the same address space so > just a pointer changes hands. THAT's why I'm saying that a separate > address space is generally a deal breaker when you have large or > intricate data sets (ie. when performance matters). Right. So use a single address space, multiple threads, and perform the heavy computations in C code. I don't see how Python is in the way at all. Many people do that, and it works just fine. That's what Jesse (probably) meant with his remark >> A c-level module, on the other hand, can sidestep/release >> the GIL at will, and go on it's merry way and process away. Please reconsider this; it might be a solution to your problem. Regards, Martin -- http://mail.python.org/mailman/listinfo/python-list
