[petsc-users] MatCreateMPIAIJWithSplitArrays

[Jed Brown]

2011/3/23 Alejandro Marcos Aragón <alejandro.aragon at gmail.com>

> My code uses a custom sparse matrix format that uses a hashed container for
> the entries of the matrix. The interface can then create a matrix in
> compressed row (or compressed column) storage format. That is, it can give
> me the three arrays needed to represent the sparse matrix in these formats.
> I would like to use the PETSc parallel solver, so then I thought that it
> would be good to try the MatCreateMPIAIJWithSplitArrays function so that I
> don't have to copy the values to the PETSc matrix again.
>

Have your hashed format generate CSR rows and insert those one row at a time
using MatSetValues(). It will be very fast and avoid the copy of using
MatCreateMPIAIJWithArrays.


>
> Now my question to you is that I really don't get the point of having a
> diagonal and off-diagonal blocks of the sparse matrix.
>

Storing the diagonal and off-diagonal part separately makes MatMult more
tolerant to network latency and permits block Jacobi preconditioning without
needing to copy out the local blocks.


> In the compressed row storage format, there is no distinction between these
> two blocks. Besides, I don't think there is a clear way to determine which
> is the boundary between these two blocks. Can someone point me how I should
> use this function, or if there is a better function that can take the three
> arrays that I have at this point?
>
> Also, since the sparse matrix in each process is the result of a finite
> element assembly routine, some rows are overlapped among the processes
> (there are several finite element nodes shared among the processes). At this
> point using the MatSetValues with the ADD_VALUES flag works fine, but I want
> to make sure that if I use the MatCreateMPIAIJWithSplitArrays (where I need
> to set the number of local rows) I can still get this behavior. In other
> words, if I sum the number of local rows in each process, I get a total
> number of rows that is greater than the number of global rows because of
> superposition.
>

Just use MatSetValues(), it will take care of parallel assembly.
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