Python multiprocessing ratio of processors and iteration

Question

This is probably a stupid question. But, if I have a simple function and I want to run it say 100 times and I have 12 processors available, is it better to use 10 processors to run the multiprocessing code or 12?

Basically by using 12 cores will I be saving one iteration time? or it will run 10 iterations in 1st time and then 2 and then 10 and so on?

Answer 1

It's almost always better to use the number of processors available. However, some algorithms need processes to communicate partial results to achieve an end result (many image processing algorithms have this constraint). Those algorithms have a limit on the number of process that should be running in parallel, as beyond this limit, the cost of communication impairs performances.

However, it depends on a lot of things. Many algorithms are easily parallelizable, however, the cost of parallelism impair their acceleration . Basically, for parallelism to be worth anything, the actual work to be done must be an order of magnitude greater than the cost of parallelism.

In typical multi-threaded languages, you can easily reduce the cost of parallelism by re-using the same threads (thread pooling). However, python being python, you must use multi-processing to achieve true parallelism, which has a huge cost. However, there's a process pool if you wish to re-use processes.

You need to check how much time it takes to run your algorithm sequentially, how much time it takes to run one iteration, and how many iteration will you have. Only then will you know if parallelization is worth it. If it is worth it, then do tests for number of processes going from 1 to 100. This will allow you to find the sweet spot for your algorithm.