title: python 3.6 multiprocessing.Pool() very slow to start using Windows
body: <p>Running Python 3.6.4 (64 bit) on Windows 10, AMD Threadripper 16 core CPU, 64 GB RAM, fast SSD. Nothing else is running (&lt;2% CPU) or using RAM (55GB Free) before I start this test. Everything runs fast except calling mp.Pool() to setup the worker processes. Once setup, running pool.map() is fast as expected. Notes: Running local and tested with and w/o virtual env. </p>
  
  <p>Any fixes, workarounds, ideas or explanations would be appreciated. Thanks.</p>
  
  <pre><code>import multiprocessing as mp
  import time
  
  for x in range(2,15):
      t0 = time.perf_counter()
      with mp.Pool(processes=x) as pool:
          pass
      print('Done {0} processes in {1:.2f}s'.format(x, time.perf_counter() - t0))
  </code></pre>
  
  <hr>
  
  <pre><code>Done 2 processes in 0.79s
  Done 3 processes in 1.34s
  Done 4 processes in 2.18s
  ...
  Done 12 processes in 6.44s
  Done 13 processes in 5.45s
  Done 14 processes in 5.73s
  </code></pre>