Hi again, I'm still reading the manual of Petsc and Slepc but at the same? I just wanted to see some vital signs that I'm on right path. The problem? that I'm trying to solve still produces the non convergence messages as? shown below.
One thing has drawn my attention, although I set the convergence tolerance? and max iterations in ESP step KSP still uses its default values I believe, such as KSP tolerances=10e-8 which is very high precision that I don't need. EPS Object: 1 MPI processes ? type not yet set ? problem type: generalized non-symmetric eigenvalue problem with symmetric pos tive definite B ? selected portion of the spectrum: not yet set ? number of eigenvalues (nev): 12 ? number of column vectors (ncv): 12 ? maximum dimension of projected problem (mpd): 0 ? maximum number of iterations: 300 ? tolerance: 0.001 ? convergence test: relative to the eigenvalue ? estimates of matrix norms (constant): norm(A)=1, norm(B)=1 IP Object: 1 MPI processes ? type not yet set ? orthogonalization method: classical Gram-Schmidt ? orthogonalization refinement: if needed (eta: 0.7071) DS Object: 1 MPI processes ? type not yet set ST Object: 1 MPI processes ? type not yet set ? shift: 0 ? matrices A and B have different nonzero pattern ? KSP Object: ?(st_) ? 1 MPI processes ? ? type not yet set ? ? maximum iterations=10000, initial guess is zero ? ? tolerances: ?relative=1e-08, absolute=1e-50, divergence=10000 ? ? left preconditioning ? ? using DEFAULT norm type for convergence test ? PC Object: ?(st_) ? 1 MPI processes ? ? type not yet set [0]PETSC ERROR: --------------------- Error Message --------------------------- -------- [0]PETSC ERROR: ? ! [0]PETSC ERROR: KSP did not converge (reason=DIVERGED_ITS)! [0]PETSC ERROR: --------------------------------------------------------------- --------
