Hi Michal,

any chance that you post or send me a small runnable test program.

By the way, there is an open PR (https://github.com/dealii/dealii/pull/9343) 
for the computation of the diagonal in a matrix-free manner. Once this is 
merged, I will work the matrix-free assembly of sparse matrices.

Thanks,
Peter

On Monday, 9 March 2020 15:26:10 UTC+1, Michał Wichrowski wrote:
>
> Dear  all,
> I've got matrix-free multigrid solver for Stokes problem. The main 
> bottleneck is solution of coarse problem, so I tried to assemble the 
> regular sparse matrix and use direct solver. Since the coarse problem is 
> (relatively) small, I used vmults by unit vector to obtain columns of the 
> matrix.  This is my code:
>
>
>     setup_matrix(); // generates sparsity patters and reinits matrices
>
> LinearAlgebra::distributed::BlockVector<LevelNumber>  dst;
> LinearAlgebra::distributed::BlockVector<LevelNumber>  src;
>
> src.reinit(2);
>     for (unsigned int b = 0; b < 2; ++b)
>     stokes_matrix.get_matrix_free()->initialize_dof_vector(
>     src.block(b), b);
>     src.collect_sizes();
>     src =0;
>
>
>     dst.reinit(2);
>     dst.block(0).reinit(owned_dofs_u, relevant_dofs_u, MPI_COMM_WORLD);
>     dst.block(1).reinit(owned_dofs_p, relevant_dofs_p, MPI_COMM_WORLD);
>     dst.collect_sizes();
>
> for(types::global_dof_index i =0; i< owned_dofs_u.size(); ++i){
> src=0;
> dst=0;
> if(owned_dofs_u.is_element(i) )
> src.block(0)(i)=1;
>
> src.compress(VectorOperation::insert);
> stokes_matrix.vmult(dst, src);
>
> dst.update_ghost_values();
>
> for(IndexSet::ElementIterator  index_iter =owned_dofs_u.begin();
> index_iter != owned_dofs_u.end();
> ++index_iter){
> if(dst.block(0)(*index_iter)!=0 )
> block_A->set(*index_iter,i, dst.block(0)(*index_iter) );
> }
>
> }
>
>     block_A->compress(VectorOperation::unknown);
>
> Without constrains the matrix matches the matrix-free operator, but with 
> constrains present it does not. What is the proper way to assemble the 
> matrix with vmult?
>
> Best,
> Michał Wichrowski
>
>
>
>

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