El 19/03/2014, a las 18:03, Oliver Browne escribió: > To Whom It May Concern, > > I am using petsc to solve an eigenvalue problem > > Jq = oq > > I am obtaining the Jacobian matrix, J, from solving > > F(x) = 0 > > and by numerically perturbing the solution to give > > J = dF(x)/dx = F(x + delta) + F(x) / delta (1) > > I use the PETSc to solve Ax=b in the Arnoldi iteration to build the > Hessenberg matrix. > > For small problems (1000 DoF) I obtain accurate results in a timely fashion > by using ILU(2) and GMRES. > > However, when I move to bigger problems (60000 Dof) I can't get the GMRES to > converge. 5 GMRES steps take an HOUR (it is incredible!!!). I have tried > modifying the levels for ILU but with no success and a few different > preconditioners. I have also tried some of the MatGetOrdering to improve the > stability. I believe that it is down to the structure of my matrix, because I > have tried similar size matrices obtained from a different code which creates > the analytical Jacobian (has a different topology), of which I can get a > convergence to GMRES in about 3 mins. I have attached a figure showing the > structure of the matrix for a smaller problem but obtained with equation (1) > above. > > I would be very grateful if you could give me some advice in choosing a > different preconditioner/solver etc or anything else which could help. > > Thanks in advance > > Olls<MatrixStructure.png>
Are you using SLEPc for the eigenvalue problem? Which eigenvalues do you want? Are you using GMRES for the shift-and-invert solve? Jose
