title: Is it possible to use BLAS to speed up sparse matrix multiplication?
body: <p>I am currently trying to speed up my large sparse (scipy) matrix multiplications. I have successfully linked my numpy installation with OpenBLAS and henceforth, also scipy. I have run these <a href="https://gist.github.com/osdf/3842524#file_test_numpy.py" rel="nofollow">tests</a> with success.</p>
  
  <p>When I use <code>numpy.dot(X,Y)</code> I can clearly see performance boosts and also that multiple cores are used simultaneously. However, when I use scipy's dot functionality, no such performance boosts can be seen and still one one core is used. For example:</p>
  
  <pre><code>x = scipy.sparse.csr_matrix(numpy.random.random((1000,1000)))
  x.dot(x.T)
  </code></pre>
  
  <p>Does anyone know how I can make BLAS also work with scipy's dot functionality?</p>