[SciPy-User] optimization with multiple processors.

[J. David Lee]

Hello everyone.

For my work I will need to perform an optimization using an objective 
function that is slow to evaluate (a few to tens of minutes). I have 
access to a virtually unlimited number of processors for my work to 
speed this up, but the optimization routines in scipy are all single 
threaded.

I see two simple ways to utilize multiple processors for newton-like or 
gradient-descent optimization methods:

1) numerical gradient or Jacobian calculation
2) line search

To some extent, parallel processing could be applied to a simplex-like 
method as well (the simplest example would be doing parallel computation 
of reflection, extension and contraction points).

I think this functionality would fit perfectly in scipy, and I will be 
working on it in any event, so if anyone would be interested in 
collaborating or providing guidance, please let me know.

Thanks,

David