Problem solved. It as user error on my part. The parallel solve was working correctly but when I was computing the functional errors, I needed to extract an array from the solution vector. Not all of the processes had finished assembling yet, so I think that caused some problems with the array.
I'm noticing though that superlu_dist is taking longer than just using PCLU in sequential. Using the time function in Mac terminal: 34.59 real 8.12 user 7.76 sys 34.59 real 8.74 user 7.87 sys 34.60 real 8.06 user 7.80 sys 34.59 real 8.84 user 7.77 sys In sequential: 17.22 real 16.79 user 0.23 sys Is this at all expected? My code is around 2x faster in parallel (on a dual core machine). I tried -pc_type redundant -redundant_pc_type lu but that didn't speed up the parallel case. On Wed, Apr 30, 2014 at 1:19 PM, Barry Smith <bsm...@mcs.anl.gov> wrote: > > Please send the same thing on one process. > > > On Apr 30, 2014, at 8:17 AM, Justin Dong <j...@rice.edu> wrote: > > > Here are the results of one example where the solution is incorrect: > > > > 0 KSP unpreconditioned resid norm 7.267616711036e-05 true resid norm > 7.267616711036e-05 ||r(i)||/||b|| 1.000000000000e+00 > > > > 1 KSP unpreconditioned resid norm 4.081398605668e-16 true resid norm > 4.017029301117e-16 ||r(i)||/||b|| 5.527299334618e-12 > > > > > > 2 KSP unpreconditioned resid norm 4.378737248697e-21 true resid norm > 4.545226736905e-16 ||r(i)||/||b|| 6.254081520291e-12 > > > > KSP Object: 4 MPI processes > > > > type: gmres > > > > GMRES: restart=30, using Classical (unmodified) Gram-Schmidt > Orthogonalization with no iterative refinement > > > > GMRES: happy breakdown tolerance 1e-30 > > > > maximum iterations=10000, initial guess is zero > > > > tolerances: relative=1e-13, absolute=1e-50, divergence=10000 > > > > right preconditioning > > > > using UNPRECONDITIONED norm type for convergence test > > > > PC Object: 4 MPI processes > > > > type: lu > > > > LU: out-of-place factorization > > > > tolerance for zero pivot 2.22045e-14 > > > > matrix ordering: natural > > > > factor fill ratio given 0, needed 0 > > > > Factored matrix follows: > > > > Matrix Object: 4 MPI processes > > > > type: mpiaij > > > > rows=1536, cols=1536 > > > > package used to perform factorization: superlu_dist > > > > total: nonzeros=0, allocated nonzeros=0 > > > > total number of mallocs used during MatSetValues calls =0 > > > > SuperLU_DIST run parameters: > > > > Process grid nprow 2 x npcol 2 > > > > Equilibrate matrix TRUE > > > > Matrix input mode 1 > > > > Replace tiny pivots TRUE > > > > Use iterative refinement FALSE > > > > Processors in row 2 col partition 2 > > > > Row permutation LargeDiag > > > > Column permutation METIS_AT_PLUS_A > > > > Parallel symbolic factorization FALSE > > > > Repeated factorization SamePattern_SameRowPerm > > > > linear system matrix = precond matrix: > > > > Matrix Object: 4 MPI processes > > > > type: mpiaij > > > > rows=1536, cols=1536 > > > > total: nonzeros=17856, allocated nonzeros=64512 > > > > total number of mallocs used during MatSetValues calls =0 > > > > using I-node (on process 0) routines: found 128 nodes, limit used > is 5 > > > > > > > > On Wed, Apr 30, 2014 at 7:57 AM, Barry Smith <bsm...@mcs.anl.gov> wrote: > > > > On Apr 30, 2014, at 6:46 AM, Matthew Knepley <knep...@gmail.com> wrote: > > > > > On Wed, Apr 30, 2014 at 6:19 AM, Justin Dong <j...@rice.edu> wrote: > > > Thanks. If I turn on the Krylov solver, the issue still seems to > persist though. > > > > > > mpiexec -n 4 -ksp_type gmres -ksp_rtol 1.0e-13 -pc_type lu > -pc_factor_mat_solver_package superlu_dist > > > > > > I'm testing on a very small system now (24 ndofs), but if I go larger > (around 20000 ndofs) then it gets worse. > > > > > > For the small system, I exported the matrices to matlab to make sure > they were being assembled correct in parallel, and I'm certain that that > they are. > > > > > > For convergence questions, always run using -ksp_monitor -ksp_view so > that we can see exactly what you run. > > > > Also run with -ksp_pc_side right > > > > > > > > > > Thanks, > > > > > > Matt > > > > > > > > > On Wed, Apr 30, 2014 at 5:32 AM, Matthew Knepley <knep...@gmail.com> > wrote: > > > On Wed, Apr 30, 2014 at 3:02 AM, Justin Dong <j...@rice.edu> wrote: > > > I actually was able to solve my own problem...for some reason, I need > to do > > > > > > PCSetType(pc, PCLU); > > > PCFactorSetMatSolverPackage(pc, MATSOLVERSUPERLU_DIST); > > > KSPSetTolerances(ksp, 1.e-15, PETSC_DEFAULT, PETSC_DEFAULT, > PETSC_DEFAULT); > > > > > > 1) Before you do SetType(PCLU) the preconditioner has no type, so > FactorSetMatSolverPackage() has no effect > > > > > > 2) There is a larger issue here. Never ever ever ever code in this > way. Hardcoding a solver is crazy. The solver you > > > use should depend on the equation, discretization, flow regime, > and architecture. Recompiling for all those is > > > out of the question. You should just use > > > > > > KSPCreate() > > > KSPSetOperators() > > > KSPSetFromOptions() > > > KSPSolve() > > > > > > and then > > > > > > -pc_type lu -pc_factor_mat_solver_package superlu_dist > > > > > > > > > instead of the ordering I initially had, though I'm not really clear > on what the issue was. However, there seems to be some loss of accuracy as > I increase the number of processes. Is this expected, or can I force a > lower tolerance somehow? I am able to compare the solutions to a reference > solution, and the error increases as I increase the processes. This is the > solution in sequential: > > > > > > Yes, this is unavoidable. However, just turn on the Krylov solver > > > > > > -ksp_type gmres -ksp_rtol 1.0e-10 > > > > > > and you can get whatever residual tolerance you want. To get a > specific error, you would need > > > a posteriori error estimation, which you could include in a custom > convergence criterion. > > > > > > Thanks, > > > > > > Matt > > > > > > superlu_1process = [ > > > -6.8035811950925553e-06 > > > 1.6324030474375778e-04 > > > 5.4145340579614926e-02 > > > 1.6640521936281516e-04 > > > -1.7669374392923965e-04 > > > -2.8099208957838207e-04 > > > 5.3958133511222223e-02 > > > -5.4077899123806263e-02 > > > -5.3972905090366369e-02 > > > -1.9485020474821160e-04 > > > 5.4239813043824400e-02 > > > 4.4883984259948430e-04]; > > > > > > superlu_2process = [ > > > -6.8035811950509821e-06 > > > 1.6324030474371623e-04 > > > 5.4145340579605655e-02 > > > 1.6640521936281687e-04 > > > -1.7669374392923807e-04 > > > -2.8099208957839834e-04 > > > 5.3958133511212911e-02 > > > -5.4077899123796964e-02 > > > -5.3972905090357078e-02 > > > -1.9485020474824480e-04 > > > 5.4239813043815172e-02 > > > 4.4883984259953320e-04]; > > > > > > superlu_4process= [ > > > -6.8035811952565206e-06 > > > 1.6324030474386164e-04 > > > 5.4145340579691455e-02 > > > 1.6640521936278326e-04 > > > -1.7669374392921441e-04 > > > -2.8099208957829171e-04 > > > 5.3958133511299078e-02 > > > -5.4077899123883062e-02 > > > -5.3972905090443085e-02 > > > -1.9485020474806352e-04 > > > 5.4239813043900860e-02 > > > 4.4883984259921287e-04]; > > > > > > This is some finite element solution and I can compute the error of > the solution against an exact solution in the functional L2 norm: > > > > > > error with 1 process: 1.71340e-02 (accepted value) > > > error with 2 processes: 2.65018e-02 > > > error with 3 processes: 3.00164e-02 > > > error with 4 processes: 3.14544e-02 > > > > > > > > > Is there a way to remedy this? > > > > > > > > > On Wed, Apr 30, 2014 at 2:37 AM, Justin Dong <j...@rice.edu> wrote: > > > Hi, > > > > > > I'm trying to solve a linear system in parallel using SuperLU but for > some reason, it's not giving me the correct solution. I'm testing on a > small example so I can compare the sequential and parallel cases manually. > I'm absolutely sure that my routine for generating the matrix and > right-hand side in parallel is working correctly. > > > > > > Running with 1 process and PCLU gives the correct solution. Running > with 2 processes and using SUPERLU_DIST does not give the correct solution > (I tried with 1 process too but according to the superlu documentation, I > would need SUPERLU for sequential?). This is the code for solving the > system: > > > > > > /* solve the system */ > > > KSPCreate(PETSC_COMM_WORLD, &ksp); > > > KSPSetOperators(ksp, Aglobal, Aglobal, > DIFFERENT_NONZERO_PATTERN); > > > KSPSetType(ksp,KSPPREONLY); > > > > > > KSPGetPC(ksp, &pc); > > > > > > KSPSetTolerances(ksp, 1.e-13, PETSC_DEFAULT, PETSC_DEFAULT, > PETSC_DEFAULT); > > > PCFactorSetMatSolverPackage(pc, MATSOLVERSUPERLU_DIST); > > > > > > KSPSolve(ksp, bglobal, bglobal); > > > > > > Sincerely, > > > Justin > > > > > > > > > > > > > > > > > > > > > -- > > > 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 > > > > > > > > > > > > > > > -- > > > 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 > > > > > >
