title: On Dask, calling sparse iterative methods Dask Array or across nodes in a cluster
body: <p>I have a large sparse matrix that can only fit on multiple nodes of a cluster. I would like to 
  solve a system of equations by calling something like </p>
  
  <pre><code>import scipy.sparse.linalg as splinalg
  
  A = my_sparse_matrix          # a sparse dask array defined across four nodes
  b = my_vector                 # an initial vector
  M = my_sparse_preconditioner  # a preconditioner to help improve convergence of algorithm
  
  x = splinalg.bicgstab(A, b, M=M)
  </code></pre>
  
  <p>Is there a way to do this so that</p>
  
  <ul>
  <li>It will solve for x in parallel if I am only using one node?</li>
  <li>Will it work if I am using more than one node (4 nodes for example)?</li>
  </ul>
  
  <p>If not, is this something that the Dask community is working on?</p>