Multithreading alternative

[MartinV279]

Inside my project I have a loop of 13 iterations which includes some feature matching. The code needs to run real time, and the only way to achieve this is by doing this loop in parallel. I tried a couple of ways to implement parallel processing with ThreadPool but there was no improvement whatsoever.

from multiprocessing.pool import ThreadPool
import multiprocessing as multip

threads = multip.Pool(multip.cpu_count())
pool = ThreadPool(threads)


def calculateParallel():
    results = pool.map(temp_match, list(range(13)))
    pool.close()
    pool.join()
    return results

where temp_match is a 30 line image processing procedure which return a ndarray.
Is there a way to go around this? From what I read online GIL makes it almost impossible to run multiple CPU threads.
I have seen a lot of posts on forums and tutorials claiming their particular code does the job, but I have not seen any improvement with any of them.
Thanks in advance!

[scidam]

ThreadPool isn't officially documented. That is, at least, one thing that could be considered suspicious.
You definitely have CPU-bound task here. From here you can find that ThreadPool isn't suitable for your task. Try to use Pool instead. Additionally, you can rewrite/optimize your 35-line image processing procedure using Cython (with no-gil clause), use numba-jit.