If you can only generate the nonzero allocation sequentially you can only solve sequentially which means your matrix is MATSEQAIJ and your vector is VECSEQ and your communicator is PETSC_COMM_SELF.
If you pass and array for nnz, what you pass for nz is irrelevant, you might as well pass 0. Barry > On Apr 18, 2018, at 10:48 AM, Klaus Burkart <k_burk...@yahoo.com> wrote: > > More questions about matrix and vector type selection for my application: > > My starting point is a huge sparse matrix which can be symmetric or > asymmetric and a rhs vector. There's no defined local or block structure at > all, just row and column indices and the values and an array style rhs vector > together describing the entire linear system to be solved. With quite some > effort, I should be able to create an array nnz[N] containing the number of > nonzeros per row in the global matrix for memory allocation which would leave > me with MatSeqAIJSetPreallocation(M, 0, nnz); as the only option for > efficient memory allocation ie. a MATSEQAIJ matrix and VECSEQ. I assume here, > that 0 indicates different numbers of nonzero values in each row, the exact > number being stored in the nnz array. Regarding this detail but one example > assume a constant number of nz per row so I am not sure whether I should > write 0 or NULL for nz? > > I started with: > > MatCreate(PETSC_COMM_WORLD, &M); > MatSetSizes(M, PETSC_DECIDE, PETSC_DECIDE, N, N); > MatSetFromOptions(M); > > taken from a paper and assume, the latter would set the matrix type to > MATSEQAIJ which might conflict with PETSC_COMM_WORLD. Maybe decompositioning > took place at an earlier stage and the authors of the paper were able to > retrieve the local data and structure. > > What type of matrix and vector should I use for my application e.g. MATSEQAIJ > and VECSEQ to be able to use MatSeqAIJSetPreallocation(M, 0, nnz); for > efficient memory allocation? > > In this case, where would the decompositioning / MPI process allocation take > place?
