On Jul 31, 7:27 pm, Craig Allen <[EMAIL PROTECTED]> wrote: > I have followed the GIL debate in python for some time. I don't want > to get into the regular debate about if it should be gotten rid of > (though I am curious about the status of that for Python 3)... > personally I think I can do multi-threaded programming well, but I > also see the benefits of a multiprocess approach. I'm not so > egotistical that I don't realize perhaps my mt programming has not > been "right" (though it worked and was debuggable) or more likely that > doing it right I have avoided even trying some things people want mt > programming to do... i.e. to do mt programming right you start to use > queues a lot, inter-threadasynchronous, non-blocking, communication, > which is essentially the multi-process approach, using IPC (except > that thethreads can see the same memory when, in your special case, > you know that's ok. Given something like a reader-writer lock, this > can have benefits... but again, whatever. > > My question is that given this problem, years ago before I started > writing in python I wrote some short programs in python which could, > in fact, busy both my CPUs. In retrospect I assume I did not have > code in my run function that causes a GIL lock... so I have done this > again. > > I start twothreads... I use gkrellm to watch my processors (dual > processor machine). If I merely print a number... both CPUS are > getting 90% simultaneous loads. If I increment a counter and print it > too, the same, and if I create a small list and sort it, the same. I > did not expect this... I expected to see one processor pegged at > around 100%, which should sometimes switch to the other processor. > Granted, the same program in C/C++ would peg both processors at > 100%... but given that the overhead in the interpreter cannot explain > the extra usage, I assume the code in mythread's run functions is > actually executing non-serially.
Try using sys.setcheckinterval(10000) (or even larger), overriding the default of 100. This will reduce the locking overhead, which might by why you see both CPUs as busy. > I assume this is because what I am doing does not require the GIL to > be locked for a significant part of the time my code is running... > what code could I put in my run function to see the behavior I > expected? What code could I put there to take advantage of the > possibility that really the GIL is not locked enough to cause actual > serialization of thethreads... anyone care to explain? The GIL is locked during *all* access to the python interpreter. There's nothing pure python code can do to avoid it - only a C extension that doesn't access python could. -- http://mail.python.org/mailman/listinfo/python-list
