Dear PETSc team, I have a few questions... During the resolution of a linear system in parallel, I am trying to apply a local LU solver to each of the SEQaij diagonal blocks of a MPIaij matrix partitioned with PARMETIS.
- I started with MUMPS but it seems that it only works with unpartitioned aij matrices, is it really the case? Or could we use MUMPS to build an additive Schwarz preconditioner for example? - Then I tried UMFPACK. This works fine when the diagonal blocks (and the memory required to store the factors) are small but crashes when they are a little bit larger. For example with a "numeric final size" of 4203.7 MBytes, I got the following message "ERROR: out of memory" while there was plenty of memory left in the computer. I tried either with the UMFPACK version 5.2, downloaded by PETSc, or with a manually installed version 5.4, linked to PETSc. Is this a behavior from UMFPACK that you already experienced? - Since UMFPACK seemed to have a memory limit around 4096 MB, I tried to install a PETSc version with the option "--with-64-bit-indices", however none of the partitioning packages could be compiled with this option (parmetis,chaco,jostle,party,scotch). Is there a way to compile PETSc with 64 bit indices AND a partitioning package? - Finally, I tried to modify the PETSc source code umfpack.c so that it would deal with 64 bit indices, but I only ended up so far with a segmentation violation message at the execution... Is it the only way I could use UMPACK with large sparse matrices? Thank you, Regards, francois pacull.
