We recommend writing a utility program that runs on one process and reads
in the files putting the values into a matrix then using MatView() with a
binary viewer to save the matrix to a file.
Then in your parallel program you simply call MatLoad() and it efficiently
loads up the matrix into your program in parallel.
This means you don't need to write a parallel reader, you only need to
write a sequential one which is easier.
Barry
> On Jul 4, 2017, at 4:22 AM, errabii sohaib <[email protected]> wrote:
>
> Hi,
>
> I am trying to use petsc4py and slepc4py to read a matrix that is distributed
> on several files, In which i save the non zero elements by specifiying three
> arrays (A, I, J) for Coeffs, rows and columns indices.
> I am currently using MUMPS and i simply read a file and pass the A,I,J arrays
> to MUMPS with each process. I am trying to do the same, however i am still
> confused how matrices are structured in PETSc and if its even possible to
> read n files and pass the matrix to PETsc to solve with slepc4py using
> atleast n processes.
>
> Thank you very much for your time,
> Sohaib.
>
>
>
