[Trilinos-Users] How to use Amesos with newton-raphson

[Neal Parsons]

I am trying to find out how to use Trilinos and Amesos/KLU with the 
nonlinear solver in NOX.  I've already implemented code using the 
didasko/examples/nox/ex1 as a template.  It uses a newton nonlinear 
solver with AztecOO's linear solver at its base, and I implemented 
custom functions to compute J and F.  I still don't have a good grasp 
on what Aztec's solver does and how it's different from 'direct' 
solvers, but at least now I know it's different.  As I wrote last week, 
a big problem we had with Aztec was that it spends a lot of time doing 
memory allocation/free and who knows what else, and there was no easy 
way I could find to reduce that overhead.  In the case of small 
systems, the overhead was overwhelming and slowed down the solver by a 
factor of at least 2 times.  Also, I had responses explaining that 
Aztec is only worth using for very large systems, and that's not my 
main focus right now.
So now I'm trying Amesos/KLU as some of the users group members 
suggested.  I've been able to get Amesos working, but only to solve 
linear systems.  I don't know if it matters whether I use the very 
simple newton-raphson algorithm in spice and call amesos/klu from 
within that, or if Trilinos (nox?  Nox/loca?) has a better 
newton-raphson algorithm.  Furthermore, I haven't seen any examples in 
the Trilinos distribution that show how to use Amesos for a non-linear 
solution.  I think that there must be a way to tie it in with NOX, and 
to define computeF and ComputeJacobian as I did with my aztec based 
project... but I haven't figured out how to do it.
Further confusing things, in the XYCE math formulation article, the 
authors claim that the voltage limiting code in circuit simulators 
prevent some of the enhancements to newton-raphson (or altogether 
different nonlinear strategies) from working.  And so even if I get 
Amesos working with an enhanced nonlinear solver, I'm suspicious that 
the effort will be wasted.
If anyone has any suggestions... let them fly!
Thanks,
Neal Parsons