Hi there,
I am trying to solve a mass matrix linear system by KSPSolve. Right now, I am
passing the mass matrix itself (let's call it M) to KSPSetOperators() as the
Pmat argument. In order to speed up the convergence, I have constructed the
lumped mass matrix (named lumpedM). For a linear finite element, this is simply
a diagonal matrix with entries equal to the sum of the row on M. It is a common
practice to replace M with lumpedM to have faster convergence without losing
the order of accuracy.
What I want to do is to still solve the M matrix but use lumpedM to
precondition it. This way hopefully the number of iterations would be greatly
reduced. In Petsc code, I tried
ierr = KSPSetOperators( solMP, M, lumpedM, SAME_PRECONDITIONER);
However, instead of giving faster convergence, it actually takes more
iterations to convergence than the regular one. Therefore, I wonder if setting
lumpedM as Pmat is the correct way to do it. Could you please advice? I think
right now lumpedM is taken as the input to compute the preconditioning matrix,
using whatever method is specified by -pc_type . What I really want to do is to
simply set lumpedM as the precondition matrix, without spending time to compute
anything.
Thank you very much.
Shi
--
Shi Jin, PhD
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