On Wed, Apr 1, 2009 at 9:46 AM, Angus Hendrick <[email protected]> wrote: > I have also found that Trilinos is about 4x faster for a 200x50 domain. > Also, in a for some problems where the standard solver gives bad results, > the Trilinos solvers give accurate results. I believe these are "stiff" > problems, but I haven't actually looked at the matrix.
We've also had the same issues with pysparse, but haven't fixed them or categorized them yet. In fact I have been experimenting with a pure python implementation of the krylov solvers using this branch <https://matforge.org/fipy/browser/branches/pykrylov> and these solvers <http://github.com/dpo/pykrylov/tree/master> This may become the default system if it isn't too slow as it would make installation way easier. > While it doesn't help for solving large domains, you can gain speed > increases on multi-core machines for embarrassingly parallel problems (i.e, > multiple separate cases) using IPython. I am currently working on a full parallel version of fipy but for grids only. Essentially the grid is divided up in a trivial way with guard cells and separate fipy jobs run on each of the subgrids. A special class assembles the global matrix. It should work very well with good scaling. Unstructured grids will be difficult and we probably won't get into that in the near future. I'll keep you posted regarding this and when we have a branch (currently it isn't even on a branch of fipy, just in a working copy) and something committed. -- Daniel Wheeler
