On Sat, Aug 29, 2020 at 3:24 PM Eda Oktay <eda.ok...@metu.edu.tr> wrote:
> Hi all,
>
> I am trying to partition a sparse matrix by using ParMETIS. I am
> converting my matrix to adjacency type and then applying partitioning.
> Default, I understood that partitioning doesn't use edge-weights. However,
> when I used the following codes I saw from ex15 and used
> "-test_use_edge_weights 1", I am getting the same results as when I don't
> consider edge weights.
>
> PetscBool use_edge_weights=PETSC_FALSE;
>
> PetscOptionsGetBool(NULL,NULL,"-test_use_edge_weights",&use_edge_weights,NULL);
> if (use_edge_weights) {
> MatPartitioningSetUseEdgeWeights(part,use_edge_weights);
>
> MatPartitioningGetUseEdgeWeights(part,&use_edge_weights);
> if (!use_edge_weights) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,
> "use_edge_weights flag does not setup correctly \n");
> }
>
> My matrix does not consist of 1s and 0s, so I want partitioning to
> consider all the nonzero elements in the matrix as edge weights. Don't
> MatPartitioningSetUseEdgeWeights and MatPartitioningGetUseEdgeWeights do
> that? Should I add something more? In the page
> of MatPartitioningSetUseEdgeWeights, it is written that "If set
> use_edge_weights to TRUE, users need to make sure legal edge weights are
> stored in an ADJ matrix.". How can I make sure of this?
>
This is a question for the ParMetis list. My memory says that the weights
need to be non-negative, and for their optimization algorithm to work, they
should be small, say < 10.
Thanks,
Matt
> I am trying to compare the use of ParMETIS with the spectral partitioning
> algorithm when I used a weighted Laplacian.
>
> Thanks!
>
> Eda
>
>
--
What most experimenters take for granted before they begin their
experiments is infinitely more interesting than any results to which their
experiments lead.
-- Norbert Wiener
https://www.cse.buffalo.edu/~knepley/ <http://www.cse.buffalo.edu/~knepley/>
