Dear mailing list, I have a question regarding memory usage in SLEPc. Specifically, I am running out of memory when solving a generalized eigenvalue problem Ax = alpha Mx. Here M is singular so we set the problem type as GNHEP and solve with Krylov-Schur method and shift-and-invert spectral transform. The matrix A come from Stokes like problem so the transform is set to use a block diagonal preconditioner B where each of the blocks (through fieldsplit) uses hypre. The solver works nicely on smaller problems in 3d (with about 100K dofs). However, upon further refinement the system size gets to millions of dofs and we run out of memory (>150GB). I find it surprising because KSP(A, B) on the same machine works without issues. When running with "-log_trace -info" I see that the memory requests before the job is killed come from the preconditioner setup
*[0] PCSetUp(): Setting up PC for first time[0] MatConvert(): Check superclass seqhypre mpiaij -> 0[0] MatConvert(): Check superclass mpihypre mpiaij -> 0[0] MatConvert(): Check specialized (1) MatConvert_mpiaij_seqhypre_C (mpiaij) -> 0[0] MatConvert(): Check specialized (1) MatConvert_mpiaij_mpihypre_C (mpiaij) -> 0* *[0] MatConvert(): Check specialized (1) MatConvert_mpiaij_hypre_C (mpiaij) -> 1* Interestingly, when solving just the problem Ax = b with B as preconditioner I don't see any calls like the above. We can get access to a larger machine but I am curious if our setup/solution strategy can be improved/optimized. Do you have any advice on how to reduce the memory footprint? Thanks and best regards, Miro
