This all looks reasonable to me. The VecScatters times are a little high but these are fast little solves (.2 seconds each).
The RAP times are very low, suggesting we could optimize parameters a bit and reduce the iteration count. These are 7 point stencils as I recall. You could try -pc_gamg_square_graph 0 (instead of 1) and you probably want '-pc_gamg_threshold 0.0'. You could also test hypre. And you should be able to improve coarse grid load imbalance with -pc_gamg_repartition. Mark On Tue, Jun 12, 2018 at 12:32 PM, Junchao Zhang <jczh...@mcs.anl.gov> wrote: > Mark, > I tried "-pc_gamg_type agg ..." options you mentioned, and also > -ksp_type cg + PETSc's default PC bjacobi. In the latter case, to reduce > execution time I called KSPSolve 100 times instead of 1000, and also > used -ksp_max_it 100. In the 36x48=1728 ranks case, I also did a test with > -log_sync. From there you can see a lot of time is spent on VecNormBarrier, > which implies load imbalance. Note VecScatterBarrie time is misleading, > since it barriers ALL ranks, but in reality VecScatter sort of syncs in a > small neighborhood. > Barry suggested trying periodic boundary condition so that the nonzeros > are perfectly balanced across processes. I will try that to see what > happens. > > --Junchao Zhang > > On Mon, Jun 11, 2018 at 8:09 AM, Mark Adams <mfad...@lbl.gov> wrote: > >> >> >> On Mon, Jun 11, 2018 at 12:46 AM, Junchao Zhang <jczh...@mcs.anl.gov> >> wrote: >> >>> I used an LCRC machine named Bebop. I tested on its Intel Broadwell >>> nodes. Each nodes has 2 CPUs and 36 cores in total. I collected data using >>> 36 cores in a node or 18 cores in a node. As you can see, 18 cores/node >>> gave much better performance, which is reasonable as routines like MatSOR, >>> MatMult, MatMultAdd are all bandwidth bound. >>> >>> The code uses a DMDA 3D grid, 7-point stencil, and defines >>> nodes(vertices) at the surface or second to the surface as boundary nodes. >>> Boundary nodes only have a diagonal one in their row in the matrix. >>> Interior nodes have 7 nonzeros in their row. Boundary processors in the >>> processor grid has less nonzero. This is one source of load-imbalance. Will >>> load-imbalance get severer at coarser grids of an MG level? >>> >> >> Yes. >> >> You can use a simple Jacobi solver to see the basic performance of your >> operator and machine. Do you see as much time spent in Vec Scatters? >> VecAXPY? etc. >> >> >>> >>> I attach a trace view figure that show activity of each ranks along the >>> time axis in one KSPSove. White color means MPI wait. You can see white >>> takes a large space. >>> >>> I don't have a good explanation why at large scale (1728 cores), >>> processors wait longer time, as the communication pattern is still 7-point >>> stencil in a cubic processor gird. >>> >>> --Junchao Zhang >>> >>> On Sat, Jun 9, 2018 at 11:32 AM, Smith, Barry F. <bsm...@mcs.anl.gov> >>> wrote: >>> >>>> >>>> Junchao, >>>> >>>> Thanks, the load balance of matrix entries is remarkably similar >>>> for the two runs so it can't be a matter of worse work load imbalance for >>>> SOR for the larger case explaining why the SOR takes more time. >>>> >>>> Here is my guess (and I know no way to confirm it). In the >>>> smaller case the overlap of different processes on the same node running >>>> SOR at the same time is lower than the larger case hence the larger case is >>>> slower because there are more SOR processes fighting over the same memory >>>> bandwidth at the same time than in the smaller case. Ahh, here is >>>> something you can try, lets undersubscribe the memory bandwidth needs, run >>>> on say 16 processes per node with 8 nodes and 16 processes per node with 64 >>>> nodes and send the two -log_view output files. I assume this is an LCRC >>>> machine and NOT a KNL system? >>>> >>>> Thanks >>>> >>>> >>>> Barry >>>> >>>> >>>> > On Jun 9, 2018, at 8:29 AM, Mark Adams <mfad...@lbl.gov> wrote: >>>> > >>>> > -pc_gamg_type classical >>>> > >>>> > FYI, we only support smoothed aggregation "agg" (the default). (This >>>> thread started by saying you were using GAMG.) >>>> > >>>> > It is not clear how much this will make a difference for you, but you >>>> don't want to use classical because we do not support it. It is meant as a >>>> reference implementation for developers. >>>> > >>>> > First, how did you get the idea to use classical? If the >>>> documentation lead you to believe this was a good thing to do then we need >>>> to fix that! >>>> > >>>> > Anyway, here is a generic input for GAMG: >>>> > >>>> > -pc_type gamg >>>> > -pc_gamg_type agg >>>> > -pc_gamg_agg_nsmooths 1 >>>> > -pc_gamg_coarse_eq_limit 1000 >>>> > -pc_gamg_reuse_interpolation true >>>> > -pc_gamg_square_graph 1 >>>> > -pc_gamg_threshold 0.05 >>>> > -pc_gamg_threshold_scale .0 >>>> > >>>> > >>>> > >>>> > >>>> > On Thu, Jun 7, 2018 at 6:52 PM, Junchao Zhang <jczh...@mcs.anl.gov> >>>> wrote: >>>> > OK, I have thought that space was a typo. btw, this option does not >>>> show up in -h. >>>> > I changed number of ranks to use all cores on each node to avoid >>>> misleading ratio in -log_view. Since one node has 36 cores, I ran with >>>> 6^3=216 ranks, and 12^3=1728 ranks. I also found call counts of MatSOR etc >>>> in the two tests were different. So they are not strict weak scaling tests. >>>> I tried to add -ksp_max_it 6 -pc_mg_levels 6, but still could not make the >>>> two have the same MatSOR count. Anyway, I attached the load balance output. >>>> > >>>> > I find PCApply_MG calls PCMGMCycle_Private, which is recursive and >>>> indirectly calls MatSOR_MPIAIJ. I believe the following code in >>>> MatSOR_MPIAIJ practically syncs {MatSOR, MatMultAdd}_SeqAIJ between >>>> processors through VecScatter at each MG level. If SOR and MatMultAdd are >>>> imbalanced, the cost is accumulated along MG levels and shows up as large >>>> VecScatter cost. >>>> > 1460: while >>>> > (its--) { >>>> > >>>> > 1461: VecScatterBegin(mat->Mvctx,xx >>>> ,mat->lvec,INSERT_VALUES,SCATTER_FORWARD >>>> > ); >>>> > >>>> > 1462: VecScatterEnd(mat->Mvctx,xx,m >>>> at->lvec,INSERT_VALUES,SCATTER_FORWARD >>>> > ); >>>> > >>>> > >>>> > 1464: /* update rhs: bb1 = bb - B*x */ >>>> > 1465: VecScale >>>> > (mat->lvec,-1.0); >>>> > >>>> > 1466: (*mat->B->ops->multadd)(mat-> >>>> > B,mat->lvec,bb,bb1); >>>> > >>>> > >>>> > 1468: /* local sweep */ >>>> > 1469: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP, >>>> > fshift,lits,1,xx); >>>> > >>>> > 1470: } >>>> > >>>> > >>>> > >>>> > --Junchao Zhang >>>> > >>>> > On Thu, Jun 7, 2018 at 3:11 PM, Smith, Barry F. <bsm...@mcs.anl.gov> >>>> wrote: >>>> > >>>> > >>>> > > On Jun 7, 2018, at 12:27 PM, Zhang, Junchao <jczh...@mcs.anl.gov> >>>> wrote: >>>> > > >>>> > > Searched but could not find this option, -mat_view::load_balance >>>> > >>>> > There is a space between the view and the : load_balance is a >>>> particular viewer format that causes the printing of load balance >>>> information about number of nonzeros in the matrix. >>>> > >>>> > Barry >>>> > >>>> > > >>>> > > --Junchao Zhang >>>> > > >>>> > > On Thu, Jun 7, 2018 at 10:46 AM, Smith, Barry F. < >>>> bsm...@mcs.anl.gov> wrote: >>>> > > So the only surprise in the results is the SOR. It is >>>> embarrassingly parallel and normally one would not see a jump. >>>> > > >>>> > > The load balance for SOR time 1.5 is better at 1000 processes than >>>> for 125 processes of 2.1 not worse so this number doesn't easily explain >>>> it. >>>> > > >>>> > > Could you run the 125 and 1000 with -mat_view ::load_balance and >>>> see what you get out? >>>> > > >>>> > > Thanks >>>> > > >>>> > > Barry >>>> > > >>>> > > Notice that the MatSOR time jumps a lot about 5 secs when the >>>> -log_sync is on. My only guess is that the MatSOR is sharing memory >>>> bandwidth (or some other resource? cores?) with the VecScatter and for some >>>> reason this is worse for 1000 cores but I don't know why. >>>> > > >>>> > > > On Jun 6, 2018, at 9:13 PM, Junchao Zhang <jczh...@mcs.anl.gov> >>>> wrote: >>>> > > > >>>> > > > Hi, PETSc developers, >>>> > > > I tested Michael Becker's code. The code calls the same KSPSolve >>>> 1000 times in the second stage and needs cubic number of processors to run. >>>> I ran with 125 ranks and 1000 ranks, with or without -log_sync option. I >>>> attach the log view output files and a scaling loss excel file. >>>> > > > I profiled the code with 125 processors. It looks {MatSOR, >>>> MatMult, MatMultAdd, MatMultTranspose, MatMultTransposeAdd}_SeqAIJ in aij.c >>>> took ~50% of the time, The other half time was spent on waiting in MPI. >>>> MatSOR_SeqAIJ took 30%, mostly in PetscSparseDenseMinusDot(). >>>> > > > I tested it on a 36 cores/node machine. I found 32 ranks/node >>>> gave better performance (about 10%) than 36 ranks/node in the 125 ranks >>>> testing. I guess it is because processors in the former had more balanced >>>> memory bandwidth. I collected PAPI_DP_OPS (double precision operations) and >>>> PAPI_TOT_CYC (total cycles) of the 125 ranks case (see the attached files). >>>> It looks ranks at the two ends have less DP_OPS and TOT_CYC. >>>> > > > Does anyone familiar with the algorithm have quick explanations? >>>> > > > >>>> > > > --Junchao Zhang >>>> > > > >>>> > > > On Mon, Jun 4, 2018 at 11:59 AM, Michael Becker < >>>> michael.bec...@physik.uni-giessen.de> wrote: >>>> > > > Hello again, >>>> > > > >>>> > > > this took me longer than I anticipated, but here we go. >>>> > > > I did reruns of the cases where only half the processes per node >>>> were used (without -log_sync): >>>> > > > >>>> > > > 125 procs,1st 125 procs,2nd >>>> 1000 procs,1st 1000 procs,2nd >>>> > > > Max Ratio Max Ratio >>>> Max Ratio Max Ratio >>>> > > > KSPSolve 1.203E+02 1.0 1.210E+02 1.0 >>>> 1.399E+02 1.1 1.365E+02 1.0 >>>> > > > VecTDot 6.376E+00 3.7 6.551E+00 4.0 >>>> 7.885E+00 2.9 7.175E+00 3.4 >>>> > > > VecNorm 4.579E+00 7.1 5.803E+00 10.2 >>>> 8.534E+00 6.9 6.026E+00 4.9 >>>> > > > VecScale 1.070E-01 2.1 1.129E-01 2.2 >>>> 1.301E-01 2.5 1.270E-01 2.4 >>>> > > > VecCopy 1.123E-01 1.3 1.149E-01 1.3 >>>> 1.301E-01 1.6 1.359E-01 1.6 >>>> > > > VecSet 7.063E-01 1.7 6.968E-01 1.7 >>>> 7.432E-01 1.8 7.425E-01 1.8 >>>> > > > VecAXPY 1.166E+00 1.4 1.167E+00 1.4 >>>> 1.221E+00 1.5 1.279E+00 1.6 >>>> > > > VecAYPX 1.317E+00 1.6 1.290E+00 1.6 >>>> 1.536E+00 1.9 1.499E+00 2.0 >>>> > > > VecScatterBegin 6.142E+00 3.2 5.974E+00 2.8 >>>> 6.448E+00 3.0 6.472E+00 2.9 >>>> > > > VecScatterEnd 3.606E+01 4.2 3.551E+01 4.0 >>>> 5.244E+01 2.7 4.995E+01 2.7 >>>> > > > MatMult 3.561E+01 1.6 3.403E+01 1.5 >>>> 3.435E+01 1.4 3.332E+01 1.4 >>>> > > > MatMultAdd 1.124E+01 2.0 1.130E+01 2.1 >>>> 2.093E+01 2.9 1.995E+01 2.7 >>>> > > > MatMultTranspose 1.372E+01 2.5 1.388E+01 2.6 >>>> 1.477E+01 2.2 1.381E+01 2.1 >>>> > > > MatSolve 1.949E-02 0.0 1.653E-02 0.0 >>>> 4.789E-02 0.0 4.466E-02 0.0 >>>> > > > MatSOR 6.610E+01 1.3 6.673E+01 1.3 >>>> 7.111E+01 1.3 7.105E+01 1.3 >>>> > > > MatResidual 2.647E+01 1.7 2.667E+01 1.7 >>>> 2.446E+01 1.4 2.467E+01 1.5 >>>> > > > PCSetUpOnBlocks 5.266E-03 1.4 5.295E-03 1.4 >>>> 5.427E-03 1.5 5.289E-03 1.4 >>>> > > > PCApply 1.031E+02 1.0 1.035E+02 1.0 >>>> 1.180E+02 1.0 1.164E+02 1.0 >>>> > > > >>>> > > > I also slimmed down my code and basically wrote a simple weak >>>> scaling test (source files attached) so you can profile it yourself. I >>>> appreciate the offer Junchao, thank you. >>>> > > > You can adjust the system size per processor at runtime via >>>> "-nodes_per_proc 30" and the number of repeated calls to the function >>>> containing KSPsolve() via "-iterations 1000". The physical problem is >>>> simply calculating the electric potential from a homogeneous charge >>>> distribution, done multiple times to accumulate time in KSPsolve(). >>>> > > > A job would be started using something like >>>> > > > mpirun -n 125 ~/petsc_ws/ws_test -nodes_per_proc 30 -mesh_size >>>> 1E-4 -iterations 1000 \\ >>>> > > > -ksp_rtol 1E-6 \ >>>> > > > -log_view -log_sync\ >>>> > > > -pc_type gamg -pc_gamg_type classical\ >>>> > > > -ksp_type cg \ >>>> > > > -ksp_norm_type unpreconditioned \ >>>> > > > -mg_levels_ksp_type richardson \ >>>> > > > -mg_levels_ksp_norm_type none \ >>>> > > > -mg_levels_pc_type sor \ >>>> > > > -mg_levels_ksp_max_it 1 \ >>>> > > > -mg_levels_pc_sor_its 1 \ >>>> > > > -mg_levels_esteig_ksp_type cg \ >>>> > > > -mg_levels_esteig_ksp_max_it 10 \ >>>> > > > -gamg_est_ksp_type cg >>>> > > > , ideally started on a cube number of processes for a cubical >>>> process grid. >>>> > > > Using 125 processes and 10.000 iterations I get the output in >>>> "log_view_125_new.txt", which shows the same imbalance for me. >>>> > > > Michael >>>> > > > >>>> > > > >>>> > > > Am 02.06.2018 um 13:40 schrieb Mark Adams: >>>> > > >> >>>> > > >> >>>> > > >> On Fri, Jun 1, 2018 at 11:20 PM, Junchao Zhang < >>>> jczh...@mcs.anl.gov> wrote: >>>> > > >> Hi,Michael, >>>> > > >> You can add -log_sync besides -log_view, which adds barriers to >>>> certain events but measures barrier time separately from the events. I find >>>> this option makes it easier to interpret log_view output. >>>> > > >> >>>> > > >> That is great (good to know). >>>> > > >> >>>> > > >> This should give us a better idea if your large VecScatter costs >>>> are from slow communication or if it catching some sort of load imbalance. >>>> > > >> >>>> > > >> >>>> > > >> --Junchao Zhang >>>> > > >> >>>> > > >> On Wed, May 30, 2018 at 3:27 AM, Michael Becker < >>>> michael.bec...@physik.uni-giessen.de> wrote: >>>> > > >> Barry: On its way. Could take a couple days again. >>>> > > >> >>>> > > >> Junchao: I unfortunately don't have access to a cluster with a >>>> faster network. This one has a mixed 4X QDR-FDR InfiniBand 2:1 blocking >>>> fat-tree network, which I realize causes parallel slowdown if the nodes are >>>> not connected to the same switch. Each node has 24 processors (2x12/socket) >>>> and four NUMA domains (two for each socket). >>>> > > >> The ranks are usually not distributed perfectly even, i.e. for >>>> 125 processes, of the six required nodes, five would use 21 cores and one >>>> 20. >>>> > > >> Would using another CPU type make a difference >>>> communication-wise? I could switch to faster ones (on the same network), >>>> but I always assumed this would only improve performance of the stuff that >>>> is unrelated to communication. >>>> > > >> >>>> > > >> Michael >>>> > > >> >>>> > > >> >>>> > > >> >>>> > > >>> The log files have something like "Average time for zero size >>>> MPI_Send(): 1.84231e-05". It looks you ran on a cluster with a very slow >>>> network. A typical machine should give less than 1/10 of the latency you >>>> have. An easy way to try is just running the code on a machine with a >>>> faster network and see what happens. >>>> > > >>> >>>> > > >>> Also, how many cores & numa domains does a compute node have? I >>>> could not figure out how you distributed the 125 MPI ranks evenly. >>>> > > >>> >>>> > > >>> --Junchao Zhang >>>> > > >>> >>>> > > >>> On Tue, May 29, 2018 at 6:18 AM, Michael Becker < >>>> michael.bec...@physik.uni-giessen.de> wrote: >>>> > > >>> Hello again, >>>> > > >>> >>>> > > >>> here are the updated log_view files for 125 and 1000 >>>> processors. I ran both problems twice, the first time with all processors >>>> per node allocated ("-1.txt"), the second with only half on twice the >>>> number of nodes ("-2.txt"). >>>> > > >>> >>>> > > >>>>> On May 24, 2018, at 12:24 AM, Michael Becker < >>>> michael.bec...@physik.uni-giessen.de> >>>> > > >>>>> wrote: >>>> > > >>>>> >>>> > > >>>>> I noticed that for every individual KSP iteration, six vector >>>> objects are created and destroyed (with CG, more with e.g. GMRES). >>>> > > >>>>> >>>> > > >>>> Hmm, it is certainly not intended at vectors be created and >>>> destroyed within each KSPSolve() could you please point us to the code that >>>> makes you think they are being created and destroyed? We create all the >>>> work vectors at KSPSetUp() and destroy them in KSPReset() not during the >>>> solve. Not that this would be a measurable distance. >>>> > > >>>> >>>> > > >>> >>>> > > >>> I mean this, right in the log_view output: >>>> > > >>> >>>> > > >>>> Memory usage is given in bytes: >>>> > > >>>> >>>> > > >>>> Object Type Creations Destructions Memory Descendants' Mem. >>>> > > >>>> Reports information only for process 0. >>>> > > >>>> >>>> > > >>>> --- Event Stage 0: Main Stage >>>> > > >>>> >>>> > > >>>> ... >>>> > > >>>> >>>> > > >>>> --- Event Stage 1: First Solve >>>> > > >>>> >>>> > > >>>> ... >>>> > > >>>> >>>> > > >>>> --- Event Stage 2: Remaining Solves >>>> > > >>>> >>>> > > >>>> Vector 23904 23904 1295501184 0. >>>> > > >>> I logged the exact number of KSP iterations over the 999 >>>> timesteps and its exactly 23904/6 = 3984. >>>> > > >>> Michael >>>> > > >>> >>>> > > >>> >>>> > > >>> Am 24.05.2018 um 19:50 schrieb Smith, Barry F.: >>>> > > >>>> >>>> > > >>>> Please send the log file for 1000 with cg as the solver. >>>> > > >>>> >>>> > > >>>> You should make a bar chart of each event for the two cases >>>> to see which ones are taking more time and which are taking less (we cannot >>>> tell with the two logs you sent us since they are for different solvers.) >>>> > > >>>> >>>> > > >>>> >>>> > > >>>> >>>> > > >>>> >>>> > > >>>>> On May 24, 2018, at 12:24 AM, Michael Becker < >>>> michael.bec...@physik.uni-giessen.de> >>>> > > >>>>> wrote: >>>> > > >>>>> >>>> > > >>>>> I noticed that for every individual KSP iteration, six vector >>>> objects are created and destroyed (with CG, more with e.g. GMRES). >>>> > > >>>>> >>>> > > >>>> Hmm, it is certainly not intended at vectors be created and >>>> destroyed within each KSPSolve() could you please point us to the code that >>>> makes you think they are being created and destroyed? We create all the >>>> work vectors at KSPSetUp() and destroy them in KSPReset() not during the >>>> solve. Not that this would be a measurable distance. >>>> > > >>>> >>>> > > >>>> >>>> > > >>>> >>>> > > >>>> >>>> > > >>>>> This seems kind of wasteful, is this supposed to be like >>>> this? Is this even the reason for my problems? Apart from that, everything >>>> seems quite normal to me (but I'm not the expert here). >>>> > > >>>>> >>>> > > >>>>> >>>> > > >>>>> Thanks in advance. >>>> > > >>>>> >>>> > > >>>>> Michael >>>> > > >>>>> >>>> > > >>>>> >>>> > > >>>>> >>>> > > >>>>> <log_view_125procs.txt><log_vi >>>> > > >>>>> ew_1000procs.txt> >>>> > > >>>>> >>>> > > >>> >>>> > > >>> >>>> > > >> >>>> > > >> >>>> > > >> >>>> > > > >>>> > > > >>>> > > > <o-wstest-125.txt><Scaling-loss.png><o-wstest-1000.txt><o-ws >>>> test-sync-125.txt><o-wstest-sync-1000.txt><MatSOR_SeqAIJ.png >>>> ><PAPI_TOT_CYC.png><PAPI_DP_OPS.png> >>>> > > >>>> > > >>>> > >>>> > >>>> > >>>> >>>> >>> >> >