On Mon, Oct 30, 2017 at 3:02 PM, Smith, Barry F. <[email protected]> wrote:
> > > On Oct 30, 2017, at 1:58 PM, Mark Lohry <[email protected]> wrote: > > > > Hmm, metis doesn't really have anything to do with the sparsity of the > Jacobian does it? > > > > No, I just mean I'm doing initial partitioning and parallel > communication for the residual evaluations independently of petsc, and then > doing a 1-to-1 mapping to the petsc solution vector. Along with manually > setting the non-zero structure of the MPIAIJ system as in the user manual. > I don't think there's anything wrong with the system structure as it gives > the same correct answer as the un-preconditioned matrix-free approach. > > > > The exact system those MatColoring times came from has size (100x100) > blocks on the diagonals corresponding to the tetrahedral cells, with those > having 4 neighbor blocks on the same row (or fewer for elements on > boundaries.) > > Hmm, are those blocks dense? If so you could benefit enormously from > using BAIJ format. > > Matt, > > Sounds like performance bugs for the parallel coloring apply > algorithms with big "diagonal blocks" > Peter wrote the JP code (I think). I tried to look at it last night, but abstraction is not present. Its not easy to see where a performance problem might lurk. I think if we care, we just have to instrument it and run this example. Personally I have never used anything but greedy, which works great. Matt > Mark, > > Could you run with -ksp_view_mat binary and send the resulting file > called binaryoutput and we can run the coloring codes local to performance > debug. > > > Barry > > > > > On Mon, Oct 30, 2017 at 1:55 PM, Smith, Barry F. <[email protected]> > wrote: > > > > > On Oct 30, 2017, at 12:39 PM, Mark Lohry <[email protected]> wrote: > > > > > > > > > > > > > > 3) Are there any hooks analogous to KSPSetPreSolve/PostSolve for the > FD computation of the jacobians, or for the computation of the > preconditioner? I'd like to get a handle on the relative costs of these. > > > > > > No, do you just want the time? You can get that from the logging; > for example -log_view > > > > > > Yes, was just thinking in regards to your suggestion of recomputing > when the number of linear iterations gets too high; I assume it's the ratio > of preconditioner cost vs linear solver cost at runtime that's the metric > of interest, and not the absolute value of either. But I'll cross that > bridge when I come to it. > > > > > > When I had asked, I was looking to see where a long pause was > happening thinking it was the FD jacobian; turned out to be before that in > MatColoringApply which seems surprisingly expensive. MATCOLORINGJP took ~15 > minutes on 32 cores on a small 153,000^2 system, with MATCOLORINGGREEDY > taking 30 seconds. Any guidance there, or is this expected? I'm not using > DM, just manually entering the sparsity resulting from a metis > decomposition of a tetrahedral mesh. > > > > Hmm, metis doesn't really have anything to do with the sparsity of > the Jacobian does it? > > > > Matt, > > > > These times are huge. What is going on? > > > > Barry > > > > > > > > > > > Thanks for the info on the lag logic, I'll play with the TS pre/post > calls for the time-accurate problems and only use LagJacobian. > > > > > > On Mon, Oct 30, 2017 at 11:29 AM, Smith, Barry F. <[email protected]> > wrote: > > > > > > > On Oct 29, 2017, at 11:50 AM, Mark Lohry <[email protected]> wrote: > > > > > > > > Thanks again Barry, I've got the preconditioners hooked up with > -snes_mf_operator and at least AMG looks to be working great on a high > order unstructured DG problem. > > > > > > > > Couple questions on the SNESSetLagJacobian + > SNESSetLagPreconditioner code flow: > > > > > > > > 1) With -snes_mf_operator, and given SNESSetLagJacobian(snes, 1) > (default) and SNESSetLagPreconditioner(snes, 2), after the first KSP solve > in a newton iteration, will it do the finite different jacobian > calculation? Or will the Jacobian only be computed when the preconditioner > lag setting demands it on the 3rd newton step? I suspect it's the latter > based on where I see the code pause. > > > > > > SNES with -snes_mf_operator will ALWAYS use the matrix-free finite > difference f(x+h) - f(x) to apply the matrix vector product. > > > > > > The LagJacobian and LagPreconditioner are not coordinated. The > first determines how often the Jacobian used for preconditioning is > recomputed and the second determines how often the preconditioner is > recomputed. > > > > > > If you are using -snes_mf_operator then it never makes sense to > have lagJacobian < lagPreconditioner since it would recompute the Jacobian > but not actually use it. It also makes no sense for lagPreconditioner < > lagJacobian because you'd be recomputing the preconditioner on the same > Jacobian. > > > > > > But actually if you don't change the Jacobian used in building the > preconditioner then when it tries to recompute the preconditioner it > determines the matrix has not changed so skips rebuilding the > preconditioner. So when using -snes_mf_operator there is really no reason > generally to set the preconditioner lag. > > > > > > > > 2) How do implicit TS and SNESSetLagPreconditioner/Persists > interact? Does the counter since-last-preconditioner-compute reset with > time steps, or does that lag counter just increment with every SNES solve > regardless of how many nonlinear solves might have happened in a given > timestep? Say lag preconditioner is 2, and a time stepper uses 3, 2, and 3 > nonlinear solves on 3 steps, is the flow > > > > > > > > (time step 1)->(update preconditioner)->(snes solve)->(snes > solve)->(update preconditioner)->(snes solve) > > > > (time step 2)->(snes solve)->(update preconditioner)->(snes solve) > > > > (time step 3)->(snes solve)->(update preconditioner)->(snes > solve)->(snes solve) > > > > > > > > or > > > > > > > > (time step 1)->(update preconditioner)->(snes solve)->(snes > solve)->(update preconditioner)->(snes solve) > > > > (time step 2)->(update preconditioner)->(snes solve)->(snes solve) > > > > (time step 3)->(update preconditioner)->(snes solve)->(snes > solve)->(update preconditioner)->(snes solve) > > > > > > > > ? > > > > > > > > I think for implicit time stepping I'd probably want the > preconditioner to be recomputed just once at the beginning of each time > step, or some multiple of that. Does that sound reasonable? > > > > > > Yes, what you want to do is completely reasonable. > > > > > > You can use SNESSetLagJacobian() and SNESSetLagJacobianPersists() > in combination to have the Jacobian recomputed ever fixed number of times; > if you set the persists flag and set LagJacobian to 10 it will recompute > the Jacobian used in the preconditioner every 10th time a new Jacobian is > needed. > > > > > > If you want to compute the new Jacobian used to build the > preconditioner once at the beginning of each new TS stage you can set > SNESSetLagJacobian() to negative -2 in the TS prestage call. There are > possibly other tricks you can do by setting the two flags at different > locations. > > > > > > An alternative to hardwiring how often the Jacobian used to build > the preconditioner is rebuilt is to rebuild based on when the > preconditioner starts "working less well". Here you could put an additional > KSPMonitor or SNESMonitor that detects if the number of linear iterations > is above a certain amount and then sets the recompute Jacobian flag to -2 > so that for the next solve it recreates the Jacobian used in building the > preconditioner. > > > > > > > > > > > > > > 3) Are there any hooks analogous to KSPSetPreSolve/PostSolve for the > FD computation of the jacobians, or for the computation of the > preconditioner? I'd like to get a handle on the relative costs of these. > > > > > > No, do you just want the time? You can get that from the logging; > for example -log_view > > > > > > > > > > > > > > > Best, > > > > Mark > > > > > > > > On Sat, Sep 23, 2017 at 3:28 PM, Mark Lohry <[email protected]> > wrote: > > > > Great, thanks Barry. > > > > > > > > On Sat, Sep 23, 2017 at 3:12 PM, Barry Smith <[email protected]> > wrote: > > > > > > > > > On Sep 23, 2017, at 12:48 PM, Mark W. Lohry <[email protected]> > wrote: > > > > > > > > > > I'm currently using JFNK in an application where I don't have a > hand-coded jacobian, and it's working well enough but as expected the > scaling isn't great. > > > > > > > > > > What is the general process for using PC with > MatMFFDComputeJacobian? Does it make sense to occasionally have petsc > re-compute the jacobian via finite differences, and then recompute the > preconditioner? Any that just need the sparsity structure? > > > > > > > > Mark > > > > > > > > Yes, this is a common approach. SNESSetLagJacobian > -snes_lag_jacobian > > > > > > > > The normal approach in SNES to use matrix-free for the operator > and use finite differences to compute an approximate Jacobian used to > construct preconditioners is to to create a sparse matrix with the sparsity > of the approximate Jacobian (yes you need a way to figure out the sparsity, > if you use DMDA it will figure out the sparsity for you). Then you use > > > > > > > > SNESSetJacobian(snes,J,J, SNESComputeJacobianDefaultColor, NULL); > > > > > > > > and use the options database option -snes_mf_operator > > > > > > > > > > > > > Are there any PCs that don't work in the matrix-free context? > > > > > > > > If you do the above you can use almost all the PC since you are > providing an explicit matrix from which to build the preconditioner > > > > > > > > > Are there any example codes I overlooked? > > > > > > > > > > Last but not least... can the Boomer-AMG preconditioner work with > JFNK? To really show my ignorance of AMG, can it actually be written as a > matrix P^-1(Ax-b)=0, , or is it just a linear operator? > > > > > > > > Again, if you provide an approximate Jacobian like above you can > use it with BoomerAMG, if you provide NO explicit matrix you cannot use > BoomerAMG or almost any other preconditioner. > > > > > > > > Barry > > > > > > > > > > > > > > Thanks, > > > > > Mark > > > > > > > > > > > > > > > > > > > > > > > > -- 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.caam.rice.edu/~mk51/>
