Missing the null space can definitely cause problems. I suggest checking unpreconditioned residuals. On Jan 8, 2012 5:13 PM, "Mohamad M. Nasr-Azadani" <mmnasr at gmail.com> wrote:
> Thanks Barry and Matt, > > Barry, > Also if you are really solving the Poisson problem you should use > multigrid; if simple geometry then geometric multigrid if complicated > geometry probably easier to use hypre BoomerAMG. No sane person solves > Poisson problem with anything but a multigrid or FFT based solver. > > In my main code, I am actually doing what you suggested, i.e. GMRES + > boomerAMG to solve for my Poisson equation. I have not used the > KSPSetNullSpace() though. > The problem is that my code (CFD, incompressible flow 3D) diverges after a > long time integration and I am trying to find out why. > The system that I have is a fairly big one, i.e. 100 million grid points > and more. > I see that pressure solution (which is obviously coupled to the velocity > field) starts showing strange behavior. > That's why I tried to first double check my pressure solver. > > Based on your experience, do you think that not using a nullspace() for > the pressure solver for that linear system size could have caused it to > diverge? > > > Matt, > 1) Matlab could be doing a lot of things. I am betting that they scale the > problem, so -pc_type jacobi. > > That could be right. The reason that I relied on the MATLAB's gmres solver > to behave exactly similar to PETSc was just their "help" saying that > ************ > X = GMRES(A,B,RESTART,TOL,MAXIT,M1,M2) use preconditioner M or M=M1*M2 > and effectively solve the system inv(M)*A*X = inv(M)*B for X. If M is > [] then a preconditioner is not applied. > ************ > > Best, > Mohamad > > On Sat, Jan 7, 2012 at 5:39 PM, Barry Smith <bsmith at mcs.anl.gov> wrote: > >> >> On Jan 7, 2012, at 4:00 PM, Mohamad M. Nasr-Azadani wrote: >> >> > Hi guys, >> > >> > I am trying to narrow down an issue with my Poisson solver. >> > I have the following problem setup >> > >> > Laplace(f) = rhs(x,z,y) >> > 0 <= x,y,z <= (Lx,Ly,Lz) >> > >> > I solve the Poisson equation in three dimensions with the analytical >> function f(x,y,z) defined by >> > >> > f(x,z,y) = cos(2*pi*x/Lx)*cos(2*pi*y/Ly)*cos(2*pi*z/Lz) + K >> > where Lx = Ly =Lz = 1.0 and K is a constant I use to set f(Lx,Ly,Lz) = >> 0.0. >> > >> > Second order descritization is used for the Poisson equation. >> > Also, Neumann boundary condition is used everywhere, but I set the >> top-right-front node's value to zero to get rid of the Nullspaced matrix >> manually. >> >> Please don't do this. That results in a unnecessaryly huge condition >> number. Use KSPSetNullSpace.() >> >> Also if you are really solving the Poisson problem you should use >> multigrid; if simple geometry then geometric multigrid if complicated >> geometry probably easier to use hypre BoomerAMG. No sane person solves >> Poisson problem with anything but a multigrid or FFT based solver. >> >> Barry >> >> > I use 20 grid points in each direction. >> > >> > The problem is: >> > I use GMRES(20) without any preconditioners (rtol = 1e-12) to solve the >> linear system. >> > It takes 77,000 iterations to converge!!!! >> > >> > For the size of only 8,000 unknowns, even though the lsys is not >> preconditioned, I guess that is a LOT of iterations. >> > Next, I setup the exact same problem in MATLAB and use their GMRES >> solver function. >> > I set the same parameters and MATLAB tells me that it converges using >> only 3870 iterations. >> > >> > I know that there might be some internal differences between MATLAB and >> PETSc's implementations of this method, but given the fact that these two >> solvers are not preconditioned, I am wondering about this big difference? >> > >> > Any ideas? >> > >> > Best, >> > Mohamad >> > >> >> > -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.mcs.anl.gov/pipermail/petsc-users/attachments/20120108/20a2592d/attachment.htm>
