[petsc-users] singular matrix solve using MAT_SHIFT_POSITIVE_DEFINITE option

[Danny Lathouwers - TNW]

Dear users,

I encountered a strange problem. I have a singular matrix P (Poisson, Neumann boundary conditions, N=4). The rhs b sums to 0.
If I hand-fill the matrix with the right entries (non-zeroes only) things work with KSPCG and ICC preconditioning and using the MAT_SHIFT_POSITIVE_DEFINITE option. Convergence in 2 iterations to (a) correct solution. So far for the debugging problem.

My real problem computes P from D * M * D^T. If I do this I get the same matrix (on std out I do not see the difference to all digits).
The system P * x = b now does NOT converge.
More strange is that is if I remove the zeroes from D then things do work again.
Either things are overly sensitive or I am misusing petsc.
It does work when using e.g. the AMG preconditioner (again it is a correct but different solution). So system really seems OK.

Should I also use the Null space commands as I have seen in some of the examples as well?
But, I recall from many years ago when using MICCG (alpha) preconditioning that no such tricks were needed for CG with Poisson-Neumann. I am supposing the MAT_SHIFT_POSITIVE_DEFINITE option does something similar as MICCG.

For clarity I have included the code (unfortunately this is the smallest I could get it; it's quite straightforward though).
By setting the value of option to 1 in main.f90 the code use P = D * M * D^T otherwise it will use the hand-filled matrix.
The code prints the matrix P and solution etc.

Anyone any hints on this?
What other preconditioners (serial) are suitable for this problem besides ICC/AMG?

Thanks very much.
Danny Lathouwers

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