Re: [petsc-users] Strange GAMG performance for mixed FE formulation

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':

Re: [petsc-users] Strange GAMG performance for mixed FE formulation

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

Re: [petsc-users] Strange GAMG performance for mixed FE formulation

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

Re: [petsc-users] Strange GAMG performance for mixed FE formulation

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

Re: [petsc-users] Strange GAMG performance for mixed FE formulation

> 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

Re: [petsc-users] Strange GAMG performance for mixed FE formulation

Mark, Using "-pc_gamg_square_graph 10" didn't change anything. I used values of 1, 10, 100, and 1000 and the performance seemed unaffected. Changing the threshold of -pc_gamg_threshold to 0.8 did decrease wall-clock time but it required more iterations. I am not really sure how I go about

Re: [petsc-users] Strange GAMG performance for mixed FE formulation

You have a very sparse 3D problem, with 9 non-zeros per row. It is coarsening very slowly and creating huge coarse grids. which are expensive to construct. The superlinear speedup is from cache effects, most likely. First try with: -pc_gamg_square_graph 10 ML must have some AI in there to do

Re: [petsc-users] Strange GAMG performance for mixed FE formulation

On Wed, Mar 2, 2016 at 5:28 PM, Justin Chang wrote: > Dear all, > > Using the firedrake project, I am solving this simple mixed poisson > problem: > > mesh = UnitCubeMesh(40,40,40) > V = FunctionSpace(mesh,"RT",1) > Q = FunctionSpace(mesh,"DG",0) > W = V*Q > > v, p =

Re: [petsc-users] Strange GAMG performance for mixed FE formulation

On 02/03/16 22:28, Justin Chang wrote: ... > Down solver (pre-smoother) on level 3 > > KSP Object: (solver_fieldsplit_1_mg_levels_3_) > linear system matrix = precond matrix: ... > Mat Object: 1 MPI processes > >

Re: [petsc-users] Strange GAMG performance for mixed FE formulation

On Wed, Mar 2, 2016 at 7:15 PM, Justin Chang wrote: > Barry, > > Attached are the log_summary output for each preconditioner. > MatPtAP takes all the time. It looks like there is no coarsening at all at the first level. Mark, can you see what is going on here? Matt >

Re: [petsc-users] Strange GAMG performance for mixed FE formulation

Justin, Do you have the -log_summary output for these runs? Barry > On Mar 2, 2016, at 4:28 PM, Justin Chang wrote: > > Dear all, > > Using the firedrake project, I am solving this simple mixed poisson problem: > > mesh = UnitCubeMesh(40,40,40) > V =

[petsc-users] Strange GAMG performance for mixed FE formulation

Dear all, Using the firedrake project, I am solving this simple mixed poisson problem: mesh = UnitCubeMesh(40,40,40) V = FunctionSpace(mesh,"RT",1) Q = FunctionSpace(mesh,"DG",0) W = V*Q v, p = TrialFunctions(W) w, q = TestFunctions(W) f = Function(Q)