On Fri, Jan 21, 2022 at 8:08 PM Barry Smith <bsm...@petsc.dev> wrote:
> > Junchao, Mark, > > Some of the logging information is non-sensible, MatMult says all > flops are done on the GPU (last column) but the GPU flop rate is zero. > > It looks like MatMult_SeqAIJKokkos() is missing > PetscLogGpuTimeBegin()/End() in fact all the operations in > aijkok.kokkos.cxx seem to be missing it. This might explain the crazy 0 GPU > flop rate. Can this be fixed ASAP? > I will add this profiling temporarily. I may use Kokkos own profiling APIs later. > > Regarding VecOps, sure looks the kernel launches are killing > performance. > > But in particular look at the VecTDot and VecNorm CPU flop > rates compared to the GPU, much lower, this tells me the MPI_Allreduce is > likely hurting performance in there also a great deal. It would be good to > see a single MPI rank job to compare to see performance without the MPI > overhead. > > > > > > > > On Jan 21, 2022, at 6:41 PM, Mark Adams <mfad...@lbl.gov> wrote: > > I am looking at performance of a CG/Jacobi solve on a 3D Q2 Laplacian > (ex13) on one Crusher node (8 GPUs on 4 GPU sockets, MI250X or is it > MI200?). > This is with a 16M equation problem. GPU-aware MPI and non GPU-aware MPI > are similar (mat-vec is a little faster w/o, the total is about the same, > call it noise) > > I found that MatMult was about 3x faster using 8 cores/GPU, that is all 64 > cores on the node, then when using 1 core/GPU. With the same size problem > of course. > I was thinking MatMult should be faster with just one MPI process. Oh > well, worry about that later. > > The bigger problem, and I have observed this to some extent with the > Landau TS/SNES/GPU-solver on the V/A100s, is that the vector operations are > expensive or crazy expensive. > You can see (attached) and the times here that the solve is dominated by > not-mat-vec: > > > ------------------------------------------------------------------------------------------------------------------------ > Event Count Time (sec) Flop > --- Global --- --- Stage ---- *Total GPU * - CpuToGpu - - > GpuToCpu - GPU > Max Ratio Max Ratio Max Ratio Mess AvgLen > Reduct %T %F %M %L %R %T %F %M %L %R *Mflop/s Mflop/s* Count Size > Count Size %F > > --------------------------------------------------------------------------------------------------------------------------------------------------------------- > 17:15 main= /gpfs/alpine/csc314/scratch/adams/petsc/src/snes/tests/data$ > grep "MatMult 400" jac_out_00*5_8_gpuawaremp* > MatMult 400 1.0 *1.2507e+00* 1.3 1.34e+10 1.1 3.7e+05 > 1.6e+04 0.0e+00 1 55 62 54 0 27 91100100 0 *668874 0* 0 > 0.00e+00 0 0.00e+00 100 > 17:15 main= /gpfs/alpine/csc314/scratch/adams/petsc/src/snes/tests/data$ > grep "KSPSolve 2" jac_out_001*_5_8_gpuawaremp* > KSPSolve 2 1.0 *4.4173e+00* 1.0 1.48e+10 1.1 3.7e+05 > 1.6e+04 1.2e+03 4 60 62 54 61 100100100100100 *208923 1094405* 0 > 0.00e+00 0 0.00e+00 100 > > Notes about flop counters here, > * that MatMult flops are not logged as GPU flops but something is logged > nonetheless. > * The GPU flop rate is 5x the total flop rate in KSPSolve :\ > * I think these nodes have an FP64 peak flop rate of 200 Tflops, so we are > at < 1%. > > Anway, not sure how to proceed but I thought I would share. > Maybe ask the Kokkos guys if the have looked at Crusher. > > Mark > > > <jac_out_001_kokkos_Crusher_5_8_gpuawarempi.txt> > > >