On Tue, Apr 14, 2020 at 2:44 PM Sajid Ali <sajidsyed2...@u.northwestern.edu> wrote:
> Hi Hong, > > Apologies for creating unnecessary confusion by continuing the old thread > instead of creating a new one. > > While I looked into converting the complex PDE formulation to a real > valued formulation in the past hoping for better performance, my concern > now is with TAO being incompatible with complex scalars. I would've > preferred to keep the complex PDE formulation as is (given that I spent > some time tuning it and it works well now) for cost function and gradient > evaluation while using TAO for the outer optimization loop. > > Using TAO has the obvious benefit of defining a multi objective cost > function, parametrized as a fit to a series of measurements and a set of > regularizers while not having to explicitly worry about differentiating the > regularizer or have to think about implementing a good optimization scheme. > But if it converting the complex formulation to a real formulation would > mean a loss of well conditioned forward solve (and increase in solving time > itself), I was wondering if it would be better to keep the complex PDE > formulation and write an optimization loop in PETSc while defining the > regularizer via a cost integrand. > > What exactly is the problem with TAO and complex? Is it only for some methods? Thanks, Matt > Thank You, > Sajid Ali | PhD Candidate > Applied Physics > Northwestern University > s-sajid-ali.github.io > -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener https://www.cse.buffalo.edu/~knepley/ <http://www.cse.buffalo.edu/~knepley/>