> On Aug 30, 2020, at 2:57 AM, Eda Oktay <eda.ok...@metu.edu.tr> wrote:
>
> Dear Matt,
>
> First of all I figured out that I asked wrongly. It's not ParMETIS giving the
> same result. It is CHACO. ParMETIS gives different results when I use edge
> weights.
>
> Thanks!
>
> Dear Barry,
>
> I am trying to partition the matrix to compare the edge cuts when it is
> partitioned with CHACO, ParMETIS and the spectral partitioning algorithm with
> the k-means clustering (I wrote this code in PETSc). In the end, I will
> conclude that if a linear system is to be solved and the coefficient matrix
> is large in size, then partitioning the coefficient matrix by using one of
> these algorithms will help one to solve the linear system faster and with
> small communication.
>
> What is forcing matrix to have all positive values? Isn't it done by using
> MatPartitioningGetUseEdgeWeights and MatPartitioningSetUseEdgeWeights?
>
> I will send the test case but I am already passing my original matrix
> directly to SetAdjacency (SymmA is my symmetric matrix with positive values):
>
> ierr = MatConvert(SymmA,MATMPIADJ,MAT_INITIAL_MATRIX,&AL);CHKERRQ(ierr);
>
> ierr = MatPartitioningCreate(MPI_COMM_WORLD,&part);CHKERRQ(ierr);
> ierr = MatPartitioningSetAdjacency(part,AL);CHKERRQ(ierr);
> ierr = MatPartitioningSetFromOptions(part);CHKERRQ(ierr);
You should not need this. Just
ierr = MatPartitioningCreate(MPI_COMM_WORLD,&part);CHKERRQ(ierr);
ierr = MatPartitioningSetAdjacency(part,SymmA);CHKERRQ(ierr);
ierr = MatPartitioningSetFromOptions(part);CHKERRQ(ierr);
MatPartitioningSetAdjacency takes any MatType directly.
>
> So, if ParMETIS gives different edge cut as it is expected,
> MatPartitioningGetUseEdgeWeights and MatPartitioningSetUseEdgeWeights works
> correctly. Why can't CHACO?
>
> Thanks!
>
> Eda
>
> Barry Smith <bsm...@petsc.dev <mailto:bsm...@petsc.dev>>, 30 Ağu 2020 Paz,
> 03:00 tarihinde şunu yazdı:
>
>
> > On Aug 29, 2020, at 2:23 PM, Eda Oktay <eda.ok...@metu.edu.tr
> > <mailto: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.
>
> You don't need to do this. Just pass your original matrix directly into
> MatPartitioningSetAdjacency() it will handle any conversions needed.
>
> Edge weights need to be positive, since they represent how much
> communication is to take place over that link. You may need to force your
> matrix to have all positive values before giving it to
> MatPartitioningSetAdjacency and using edge weights.
>
> I this doesn't work than our code is broken, please send us a simple test
> case
>
> Question: Why are you partitioning a matrix? Is it for load balancing of
> solves or matrix vector products with the matrix? To reduce interprocess
> communication during solves or matrix vector products with the matrix? If so
> the numerical values in the matrix don't affect load balance or interprocess
> communication for these operations.
>
>
> Barry
>
>
>
>
> > 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?
> >
> > I am trying to compare the use of ParMETIS with the spectral partitioning
> > algorithm when I used a weighted Laplacian.
> >
> > Thanks!
> >
> > Eda
> >
>
