For square matrices almost always n is the same as m. On different processes 
m can be different. You get to decide what makes sense for each processes what 
its m should be.

   Barry


> On Apr 20, 2018, at 10:05 AM, Klaus Burkart <[email protected]> wrote:
> 
> I think I understood the matrix structure for parallel computation with the 
> rows, diagonal (d) and off-diagonal (o) structure, where I have problems is 
> how to do the setup including memory allocation in PETSc:
> 
> Lets assume, I use a 16 core workstation (=16 processes) and the number of 
> nonzeros varies in each row for both d and o and the number of rows assigned 
> to each process differs too - at least for the nth process.
> 
> Looking at the manual and 
> http://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/Mat/MatCreateAIJ.html#MatCreateAIJ,
>  I don't understand how to enter a global matrix when n is NOT the same for 
> each process as e.g. in MatSetSizes(A, m,n,M,N); n and m are integers, not 
> arrays?
> 
>     MatCreate(...,&A);
> 
>     MatSetType(A,MATMPIAIJ);
> 
>     MatSetSizes(A, m,n,M,N); // seems to assume n and m are the same for each 
> process which isn't even the case in the example on the page mentioned above?!
> 
>     MatMPIAIJSetPreallocation(A,...);
> 
> 
> How can I enter the parallel global-local matrix structure?
> 
> How can the memory preallocation be done?
> 
> Klaus
> 
> Am Donnerstag, 19. April 2018, 01:47:59 MESZ hat Smith, Barry F. 
> <[email protected]> Folgendes geschrieben:
> 
> 
> 
> 
> > On Apr 18, 2018, at 4:42 PM, [email protected] wrote:
> > 
> > So, practically speaking, l should invent routines to decompose the matrix 
> > e.g. into a block matrix structure to be able to make real use of PETSc ie. 
> > be able to solve a linear system using more than one process/core?
> 
>   To really use PETSc efficiently/effectively you need to generate your 
> matrix in parallel.
> 
>   Barry
> 
> > 
> > Klaus
> > 
> > Von meinem Huawei-Mobiltelefon gesendet
> > 
> > 
> > -------- Originalnachricht --------
> > Betreff: Re: [petsc-users] Matrix and vector type selection & memory 
> > allocation for efficient matrix import?
> > Von: "Smith, Barry F." 
> > An: Klaus Burkart 
> > Cc: PETSc Users List 
> > 
> > 
> > 
> > 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 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?
> > 

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