Sorry, I really meant *parallel* execution of Python code: Multiple threads simultaneously executing a Python program, potentially on different CPUs.
There cannot be parallel threads on a single CPU - for threads to be truly parallel, you *must* have two CPUs, at a minimum.
Python threads can run truly parallel, as long as one of them invoke BEGIN_ALLOW_THREADS.
What I was trying to ask with my last email was what are the trouble areas? There are probably many that I am unaware of, due to my unfamiliarity the Python internals.
I think nobody really remembers - ask Google for "Python free threading". Greg Stein did the patch, and the main problem apparently
was that the performance became unacceptable - apparently primarily
because of dictionary locking.
Right, but as said in a previous post, I'm not convinced that the current implementation is completely correct anyway.
Why do you think so? (I see in your previous post that you claim it is not completely correct, but I don't see any proof).
Wouldn't it be up to the programmer to ensure that accesses to shared objects, like containers, are serialized?
In a truly parallel Python, two arbitrary threads could access the same container, and it would still work. If some containers cannot be used simultaneously in multiple threads, this might ask for a desaster.
For example, with Java's collections, there are both synchronized and unsynchronized versions.
I don't think this approach can apply to Python. Python users are used to completely thread-safe containers, and lots of programs would break if the container would suddenly throw exceptions.
Furthermore, the question is what kind of failure you'ld expect if an unsynchronized dictionary is used from multiple threads. Apparently, Java guarantees something (e.g. that the interpreter won't crash) but even this guarantee would be difficult to make.
For example, for lists, the C API allows direct access to the pointers in the list. If the elements of the list could change in-between, an object in the list might go away after you got the pointer, but before you had a chance to INCREF it. This would cause a crash shortly afterwards. Even if that was changed to always return a new refence, lots of code would break, as it would create large memory leaks (code would have needed to decref the list items, but currently doesn't - nor is it currently necessary).
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
