title: Dask: Jobs on multiple nodes with one worker, run on one node only
body: <p>I am trying to process some files using a python function and would like to parallelize the task on a PBS cluster using dask. On the cluster I can only launch one job but have access to 10 nodes with 24 cores each.</p>
  
  <p>So my dask PBSCluster looks like:</p>
  
  <pre><code>import dask
  from dask_jobqueue import PBSCluster
  cluster = PBSCluster(cores=240,
                       memory="1GB",
                       project='X',
                       queue='normal',
                       local_directory='$TMPDIR',
                       walltime='12:00:00',
                      resource_spec='select=10:ncpus=24:mem=1GB',
                      )
  cluster.scale(1) # one worker 
  from dask.distributed import Client
  client = Client(cluster)     
  client
  
  </code></pre>
  
  <p>After the Cluster in Dask shows 1 worker with 240 cores (not sure if that make sense). 
  When I run </p>
  
  <pre><code>result = compute(*foo, scheduler='distributed') 
  
  </code></pre>
  
  <p>and access the allocated nodes only one of them is actually running the computation. I am not sure if I using the right PBS configuration.</p>