On Thu, Sep 24, 2020 at 12:48 PM Zhang, Chonglin <zhang...@rpi.edu> wrote:
> Thanks Mark and Barry!
>
> A quick try of using “-pc_type jacobi” did reduce the number of count for
> “CpuToGpu” and “GpuToCpu”, although using “-pc_type gamg” (the counts did
> not decrease in this case) solves the problem faster (may not be of any
> meaning since the problem size is too small; the function
> “DMPlexCreateFromCellListParallelPetsc()" is slow for large problem size
> preventing running larger problems, separate issue).
>
It sounds like something is wrong then, or I do not understand what you
mean by slow.
Thanks,
Matt
> Would this “CpuToGpu” and “GpuToCpu” data transfer contribute a
> significant amount of time for a realistic sized problem, say for example a
> linear problem with ~1-2 million DOFs?
>
> Also, is there any plan to have the SNES and DMPlex code run on GPU?
>
> Thanks!
> Chonglin
>
> On Sep 24, 2020, at 12:17 PM, Barry Smith <bsm...@petsc.dev> wrote:
>
>
> MatSOR() runs on the CPU, this causes copy to CPU for each application
> of MatSOR() and then a copy to GPU for the next step.
>
> You can try, for example -pc_type jacobi better yet use PCGAMG if it
> amenable for your problem.
>
> Also the problem is way to small for a GPU.
>
> There will be copies between the GPU/CPU for each SNES iteration since
> the DMPLEX code does not run on GPUs.
>
> Barry
>
>
>
> On Sep 24, 2020, at 10:08 AM, Zhang, Chonglin <zhang...@rpi.edu> wrote:
>
> Dear PETSc Users,
>
> I have some questions regarding the proper GPU usage. I would like to know
> the proper way to:
> (1) solve linear equation in SNES, using GPU in PETSc; what
> syntax/arguments should I be using;
> (2) how to avoid/reduce the “CpuToGpu count” and “GpuToCpu count” data
> transfer showed in PETSc log file, when using CUDA aware MPI.
>
>
> Details of what I am doing now and my observations are below:
>
> System and compilers used:
> (1) RPI’s AiMOS computer (node wise, it is the same as Summit);
> (2) using GCC 7.4.0 and Spectrum-MPI 10.3.
>
> I am doing the followings to solve the linear Poisson equation with SNES
> interface, under DMPlex:
> (1) using DMPlex to set up the unstructured mesh;
> (2) using DM to create vector and matrix;
> (3) using SNES interface to solve the linear Poisson equation, with
> “-snes_type ksponly”;
> (4) using “dm_vec_type cuda”, “dm_mat_type aijcusparse “ to use GPU vector
> and matrix, as suggested in this webpage:
> https://www.mcs.anl.gov/petsc/features/gpus.html
> (5) using “use_gpu_aware_mpi” with PETSc, and using `mpirun -gpu` to
> enable GPU-Direct ( similar as "srun --smpiargs=“-gpu”" for Summit):
> https://secure.cci.rpi.edu/wiki/Slurm/#gpu-direct;
> https://www.olcf.ornl.gov/wp-content/uploads/2018/11/multi-gpu-workshop.pdf
> (6) using “-options_left” to check and make sure all the arguments are
> accepted and used by PETSc.
> (7) After problem setup, I am running the “SNESSolve()” multiple times to
> solve the linear problem and observe the log file with “-log_view"
>
> I noticed that if I run “SNESSolve()” 500 times, instead of 50 times, the
> “CpuToGpu count” and/or “GpuToCpu count” increased roughly 10 times for
> some of the operations: SNESSolve, MatSOR, VecMDot, VecCUDACopyTo,
> VecCUDACopyFrom, MatCUSPARSCopyTo. See below for a truncated log
> corresponding to running SNESSolve() 500 times:
>
>
> 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
>
> ---------------------------------------------------------------------------------------------------------------------------------------------------------------
>
> --- Event Stage 0: Main Stage
>
> BuildTwoSided 510 1.0 4.9205e-03 1.1 0.00e+00 0.0 3.5e+01 4.0e+00
> 1.0e+03 0 0 0 0 0 0 0 21 0 0 0 0 0 0.00e+00 0
> 0.00e+00 0
> BuildTwoSidedF 501 1.0 1.0199e-02 1.4 0.00e+00 0.0 0.0e+00 0.0e+00
> 1.0e+03 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00e+00 0
> 0.00e+00 0
> SNESSolve 500 1.0 3.2570e+02 1.0 1.18e+10 1.0 0.0e+00 0.0e+00
> 8.7e+05100100 0 0100 100100 0 0100 144 202 31947 7.82e+02 63363
> 1.44e+03 82
> SNESSetUp 1 1.0 6.0082e-04 1.7 0.00e+00 0.0 0.0e+00 0.0e+00
> 1.0e+00 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00e+00 0
> 0.00e+00 0
> SNESFunctionEval 500 1.0 3.9826e+01 1.0 3.60e+08 1.0 0.0e+00 0.0e+00
> 5.0e+02 12 3 0 0 0 12 3 0 0 0 36 13 0 0.00e+00 1000
> 2.48e+01 0
> SNESJacobianEval 500 1.0 4.8200e+01 1.0 5.97e+08 1.0 0.0e+00 0.0e+00
> 2.0e+03 15 5 0 0 0 15 5 0 0 0 50 0 1000 7.77e+01 500
> 1.24e+01 0
> DMPlexResidualFE 500 1.0 3.6923e+01 1.1 3.56e+08 1.0 0.0e+00 0.0e+00
> 0.0e+00 10 3 0 0 0 10 3 0 0 0 39 0 0 0.00e+00 500
> 1.24e+01 0
> DMPlexJacobianFE 500 1.0 4.6013e+01 1.0 5.95e+08 1.0 0.0e+00 0.0e+00
> 2.0e+03 14 5 0 0 0 14 5 0 0 0 52 0 1000 7.77e+01 0
> 0.00e+00 0
> MatSOR 30947 1.0 3.1254e+00 1.1 1.21e+09 1.0 0.0e+00 0.0e+00
> 0.0e+00 1 10 0 0 0 1 10 0 0 0 1542 0 0 0.00e+00 61863
> 1.41e+03 0
> MatAssemblyBegin 511 1.0 5.3428e+00256.4 0.00e+00 0.0 0.0e+00 0.0e+00
> 2.0e+03 1 0 0 0 0 1 0 0 0 0 0 0 0 0.00e+00 0
> 0.00e+00 0
> MatAssemblyEnd 511 1.0 4.3440e-02 1.2 0.00e+00 0.0 0.0e+00 0.0e+00
> 2.1e+01 0 0 0 0 0 0 0 0 0 0 0 0 1002 7.80e+01 0
> 0.00e+00 0
> MatCUSPARSCopyTo 1002 1.0 3.6557e-02 1.2 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 0 1002 7.80e+01 0
> 0.00e+00 0
> VecMDot 29930 1.0 3.7843e+01 1.0 2.62e+09 1.0 0.0e+00 0.0e+00
> 6.0e+04 12 22 0 0 7 12 22 0 0 7 277 3236 29930 6.81e+02 0
> 0.00e+00 100
> VecNorm 31447 1.0 2.1164e+01 1.4 1.79e+08 1.0 0.0e+00 0.0e+00
> 6.3e+04 5 2 0 0 7 5 2 0 0 7 34 55 1017 2.31e+01 0
> 0.00e+00 100
> VecNormalize 30947 1.0 2.3957e+01 1.1 2.65e+08 1.0 0.0e+00 0.0e+00
> 6.2e+04 7 2 0 0 7 7 2 0 0 7 44 51 1017 2.31e+01 0
> 0.00e+00 100
> VecCUDACopyTo 30947 1.0 7.8866e+00 3.4 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 2 0 0 0 0 2 0 0 0 0 0 0 30947 7.04e+02 0
> 0.00e+00 0
> VecCUDACopyFrom 63363 1.0 1.0873e+00 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00e+00 63363
> 1.44e+03 0
> KSPSetUp 500 1.0 2.2737e-03 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
> 5.0e+00 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00e+00 0
> 0.00e+00 0
> KSPSolve 500 1.0 2.3687e+02 1.0 1.08e+10 1.0 0.0e+00 0.0e+00
> 8.6e+05 72 92 0 0 99 73 92 0 0 99 182 202 30947 7.04e+02 61863
> 1.41e+03 89
> KSPGMRESOrthog 29930 1.0 1.8920e+02 1.0 7.87e+09 1.0 0.0e+00 0.0e+00
> 6.4e+05 58 67 0 0 74 58 67 0 0 74 166 209 29930 6.81e+02 0
> 0.00e+00 100
> PCApply 30947 1.0 3.1555e+00 1.1 1.21e+09 1.0 0.0e+00 0.0e+00
> 0.0e+00 1 10 0 0 0 1 10 0 0 0 1527 0 0 0.00e+00 61863
> 1.41e+03 0
>
>
> Thanks!
> Chonglin
>
>
>
>
--
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/>
