[petsc-users] Proper GPU usage in PETSc

Barry Smith bsmith at petsc.dev
Thu Sep 24 11:17:51 CDT 2020


   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 <zhangc20 at 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 <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://secure.cci.rpi.edu/wiki/Slurm/#gpu-direct>; https://www.olcf.ornl.gov/wp-content/uploads/2018/11/multi-gpu-workshop.pdf <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

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