Dear all,
What could be the benefit of iterative solvers(specifically cg or pcg),
as a factor, in comparison to direct solvers, on reasonably large sparse
systems if one has a well conditioned operator matrix.
This question might be a bit abstract(like the one above) though I will
fire anyway
For sparse problems coming from a N = n by n by n 3D grid discretization of
PDEs direct solvers end up requiring n^4 memory and n^6 = N^2 work. The best
iterative solvers (for example multigrid) if they work well on the problem
require only n^3 = N memory and n^3 = N work. So for largish n
I don't understand the code change - but if you want to use c99
complex - you can build petsc with:
--with-scalar-type=complex --with-clanguage=c [which is the default for
clanguage]
And no code-change needed for PETSc. However if your code uses c++ -
you might have to address that..
Satish
