Dear all, I want to extract the lowest eigenvalues of a huge generalized eigenvalue problem with very dense clusters of eigenvalues. I use slepc and superlu as external direct solver with the following options
-eps_ncv 300 -eps_nev 220 -eps_tol 1e-10 -st_ksp_rtol 1e-14 -st_ksp_type preonly -st_pc_type lu -st_pc_factor_mat_solver_package superlu_dist Without shift-and-invert, this simply takes way too long, even on 48 CPUs it runs for hours. If I use a shift-and-invert technique additionally invoking -st_type sinvert -st_shift -0.41, it converges very fast and also parallelizes well, but I most likely don't get the lowest eigenvalues if st_shift is slightly too high. If it's slightly too low, it doesn't seem to converge. Can anybody give me some hints on how to tweak the options? If a 100MB tar ball is not too much for you, the matrix is here: www.phys.ethz.ch/~cmay/binaryoutput.tgz Thanks in advance Christian
