[petsc-dev] Kokkos/Crusher perforance

[Barry Smith]

   Matt is correct, vectors are way too small.

   BTW: Now would be a good time to run some of the Report I benchmarks on Crusher to get a feel for the kernel launch times and performance on VecOps.

   Also Report 2.

  Barry


> On Jan 21, 2022, at 7:58 PM, Matthew Knepley <knepley at gmail.com> wrote:
> 
> On Fri, Jan 21, 2022 at 6:41 PM Mark Adams <mfadams at lbl.gov <mailto:mfadams at 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%.
> 
> This looks complicated, so just a single remark:
> 
> My understanding of the benchmarking of vector ops led by Hannah was that you needed to be much
> bigger than 16M to hit peak. I need to get the tech report, but on 8 GPUs I would think you would be
> at 10% of peak or something right off the bat at these sizes. Barry, is that right?
> 
>   Thanks,
> 
>      Matt
>  
> Anway, not sure how to proceed but I thought I would share.
> Maybe ask the Kokkos guys if the have looked at Crusher.
> 
> 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.cse.buffalo.edu/~knepley/>

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.mcs.anl.gov/pipermail/petsc-dev/attachments/20220121/8ea48552/attachment-0001.html>