Is your B-matrix singular? Then the solver might be approximating an infinite eigenvalue even if you ask for smallest real eigenvalues. For Lanczos-type solvers, it is safer to run with -st_type sinvert -eps_target 0 if you know that eigenvalues are positive. Or instead of 0 use a target value that bounds the eigenvalues from below.
Also, it is better to use Krylov-Schur instead of Lanczos, for symmetric problems it will run Lanczos with implicit restart - the 'lanczos' solver is Lanczos with explicit restart (usually worse). Jose > El 5 may 2019, a las 17:05, Qiyue Lu via petsc-users > <petsc-users@mcs.anl.gov> escribió: > > Hello, > I am solving a general eigenvalue problem > Ax=lamda*Bx > A is the stiffness matrix, B the mass matrix. The DOF of these matrices are > 24,000 around. Both of them are symmetric and stored in SEQSBAIJ format. > Also, I downloaded mumps during the configuration and installation of PETSc. > In SLETc, this eigenvalue system can be solved by -eps_tpye logpcg while > requesting EPS_SMALLEST_REAL. However, -eps_type lanczos doesn't work, which > yields a very huge number. It seems mumps is called indeed. The output of > -eps_view is attached. The command line I am using is: > mpirun -np 40 ./test -fA matrixA -fB matrixB -eps_type lanczos -eps_view > > Did I miss any substantial configurations for lanczos solver? > > Thanks, > > Qiyue Lu > <test10B_bash.out>
