Python multiprocessing run time per process increases with number of processes
问题 I have a pool of workers which perform the same identical task, and I send each a distinct clone of the same data object. Then, I measure the run time separately for each process inside the worker function. With one process, run time is 4 seconds. With 3 processes, the run time for each process goes up to 6 seconds. With more complex tasks, this increase is even more nuanced. There are no other cpu-hogging processes running on my system, and the workers don't use shared memory (as far as I