1. Do the same as in code2.py using only Process and Queue.
   - You should run not more than ncores process at once
   - You can use multiprocessing.cpu_count to take number of cores
   - code4.py is an example of solution, but first, try to do it by yourself

2. Test performance of your code and compare it with performance of
   code2.py which use Pool+map. You will find that your solution is a
   little bit slower than code2.py .

3. Read about "chunksize" parameter of map
   (https://docs.python.org/3/library/multiprocessing.html). By
   default map set chunksize in such a way that each process get
   approximately 4 chunks.

4. Modify your code by including chunksize parameter. Compare
   performance of your new code with code2.py.
