mk <mrk...@gmail.com> wrote: > This time I decided to test communication overhead in multithreaded / > multiprocess communication. The results are rather disappointing, that > is, communication overhead seems to be very high. In each of the > following functions, I send 10,000 numbers to the function / 10 threads > / 10 processes, which simply returns it in its respective way. > > > Function: notfun Best: 0.00622 sec Average: 0.00633 sec > (simple function) > > Function: threadsemfun Best: 0.64428 sec Average: 0.64791 sec > (10 threads synchronizing using semaphore) > > Function: threadlockfun Best: 0.66288 sec Average: 0.66453 sec > (10 threads synchronizing using locks) > > Function: procqueuefun Best: 1.16291 sec Average: 1.17217 sec > (10 processes communicating with main process using queues) > > Function: procpoolfun Best: 1.18648 sec Average: 1.19577 sec > (a pool of 10 processes) > > If I'm doing smth wrong in the code below (smth that would result in > performance suffering), please point it out.
You aren't just timing the communication overhead: each of your functions creates a pool of 10 threads or 10 processes on every run, so your times include the startup and shutdown times. -- http://mail.python.org/mailman/listinfo/python-list
