Hello, I am trying to use petsc4py and slepc4py for parallel sparse matrix diagonalization. However I am a bit confused about matrix size increase when I switch from single processor to multiple processors. For example 100 x 100 matrix with 298 nonzero elements consumes 8820 bytes of memory (mat.getInfo()["memory"]), however on two processes it consumes 20552 bytes of memory and on four 33528. My matrix is taken from the slepc4py/demo/ex1.py, where nonzero elements are on three diagonals.
Why memory usage increases with MPI processes number? I thought that each process stores its own rows and it should stay the same. Or some elements are stored globally? Lukas
