title: Using python's multiprocessing on slurm
body: <p>I am trying to run some parallel code on slurm, where the different processes do not need to communicate. Naively I used python's slurm package. However, it seems that I am only using the cpu's on one node.</p>
  
  <p>For example, if I have 4 nodes with 5 cpu's each, I will only run 5 processes at the same time. How can I tell multiprocessing to run on different nodes?</p>
  
  <p>The python code looks like the following</p>
  
  <pre><code>import multiprocessing
  
  def hello():
      print("Hello World")
  
  pool = multiprocessing.Pool() 
  jobs = [] 
  for j in range(len(10)):
      p = multiprocessing.Process(target = run_rel)
      jobs.append(p)
      p.start() 
  </code></pre>
  
  <p>The problem is similar to <a href="https://stackoverflow.com/questions/32594734/slurm-multiprocessing-python-job">this one</a>, but there it has not been solved in detail.</p>