title: Is there a parallelized version of scipy.optimize.minimize?
body: <p>I am trying to minimize a cost function using <code>scipy.optimize.minimize</code>, but it is very slow. My function has close to 5000 variables, and so it is not surprising that scipy is slow. However, if there is a parallel version of <code>scipy.optimize.minimize</code> it might help a great deal.</p>
  
  <p>I was wondering if such version of <code>scipy.optimize.minimize</code> exists or if there is any other scipy/numpy tool available for performing minimization of this magnitude. I really appreciate any and all help.</p>
  
  <p>Thanks everybody for their comments. This is a constrained minimization using the SLSQP solver. I have already spent a lot of time making sure that the cost function calculation is optimized, so the problem must be in calculation of the gradient or due to constraints. In other words, the amount of time that is spent on function evaluations is a very small fraction of the total time spent on the minimization. </p>