And it looks like you have a well behaved Laplacian here (M-matrix) so I
would guess 'richardson' would be faster as the smoother, instead of
'chebyshev'.
On Fri, Mar 4, 2016 at 5:04 PM, Mark Adams wrote:
> You seem to have 3 of one type of solve that is give 'square_graph 1':
You seem to have 3 of one type of solve that is give 'square_graph 1':
0] PC*GAMG*Coarsen_AGG(): Square Graph on level 1 of 1 to square
This has 9 nnz-row and 44% are zero:
[0] PC*GAMG*FilterGraph(): 55.7114% nnz after filtering, with threshold
0., 8.79533 nnz ave.
So you want to use a
On Fri, Mar 4, 2016 at 8:25 AM, Alejandro D Otero wrote:
> Hello, I am trying to save some field stored in a vector which has values
> associated with vertexes, edges and cells in a DMPlex.
> This vector was created (using petsc4py) from a petcs section, setting
> this as
You're right. This is what I have:
[0] PCSetUp_*GAMG*(): level 0) N=48000, n data rows=1, n data cols=1,
nnz/row (ave)=9, np=1
[0] PC*GAMG*FilterGraph(): 55.7114% nnz after filtering, with threshold
0., 8.79533 nnz ave. (N=48000)
[0] PC*GAMG*Coarsen_AGG(): Square Graph on level 1 of 1 to
Time to solution went from 100 seconds to 30 seconds once i used 10 graphs.
Using 20 graphs started to increase in time slightly
On Fri, Mar 4, 2016 at 8:35 AM, Justin Chang wrote:
> You're right. This is what I have:
>
> [0] PCSetUp_*GAMG*(): level 0) N=48000, n data
> On 4 Mar 2016, at 15:24, Justin Chang wrote:
>
> So with -pc_gamg_square_graph 10 I get the following:
Because you're using gamg inside the fieldsplit, I think you need:
-fieldsplit_1_pc_gamg_square_graph 10
> [0] PCSetUp_GAMG(): level 0) N=48000, n data rows=1, n