[petsc-dev] MatMult on Summit

Zhang, Junchao jczhang at mcs.anl.gov
Fri Sep 20 23:39:39 CDT 2019


Click the links to visualize it.

6 ranks
https://jsrunvisualizer.olcf.ornl.gov/?s4f1o01n6c1g1r11d1b21l0=
jsrun -n 6 -a 1 -c 1 -g 1 -r 6 --latency_priority GPU-GPU --launch_distribution packed --bind packed:1 js_task_info ./ex900 -f HV15R.aij -mat_type aijcusparse -vec_type cuda -n 100 -log_view

24 ranks
https://jsrunvisualizer.olcf.ornl.gov/?s4f1o01n6c4g1r14d1b21l0=
jsrun -n 6 -a 4 -c 4 -g 1 -r 6 --latency_priority GPU-GPU --launch_distribution packed --bind packed:1 js_task_info ./ex900 -f HV15R.aij -mat_type aijcusparse -vec_type cuda -n 100 -log_view

--Junchao Zhang


On Fri, Sep 20, 2019 at 11:34 PM Mills, Richard Tran via petsc-dev <petsc-dev at mcs.anl.gov<mailto:petsc-dev at mcs.anl.gov>> wrote:
Junchao,

Can you share your 'jsrun' command so that we can see how you are mapping things to resource sets?

--Richard

On 9/20/19 11:22 PM, Zhang, Junchao via petsc-dev wrote:
I downloaded a sparse matrix (HV15R<https://sparse.tamu.edu/Fluorem/HV15R>) from Florida Sparse Matrix Collection. Its size is about 2M x 2M. Then I ran the same MatMult 100 times on one node of Summit with -mat_type aijcusparse -vec_type cuda. I found MatMult was almost dominated by VecScatter in this simple test. Using 6 MPI ranks + 6 GPUs,  I found CUDA aware SF could improve performance. But if I enabled Multi-Process Service on Summit and used 24 ranks + 6 GPUs, I found CUDA aware SF hurt performance. I don't know why and have to profile it. I will also collect  data with multiple nodes. Are the matrix and tests proper?

------------------------------------------------------------------------------------------------------------------------
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
---------------------------------------------------------------------------------------------------------------------------------------------------------------
6 MPI ranks (CPU version)
MatMult              100 1.0 1.1895e+01 1.0 9.63e+09 1.1 2.8e+03 2.2e+05 0.0e+00 24 99 97 18  0 100100100100  0  4743       0      0 0.00e+00    0 0.00e+00  0
VecScatterBegin      100 1.0 4.9145e-02 3.0 0.00e+00 0.0 2.8e+03 2.2e+05 0.0e+00  0  0 97 18  0   0  0100100  0     0       0      0 0.00e+00    0 0.00e+00  0
VecScatterEnd        100 1.0 2.9441e+00133  0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00  3  0  0  0  0  13  0  0  0  0     0       0      0 0.00e+00    0 0.00e+00  0

6 MPI ranks + 6 GPUs + regular SF
MatMult              100 1.0 1.7800e-01 1.0 9.66e+09 1.1 2.8e+03 2.2e+05 0.0e+00  0 99 97 18  0 100100100100  0 318057   3084009 100 1.02e+02  100 2.69e+02 100
VecScatterBegin      100 1.0 1.2786e-01 1.3 0.00e+00 0.0 2.8e+03 2.2e+05 0.0e+00  0  0 97 18  0  64  0100100  0     0       0      0 0.00e+00  100 2.69e+02  0
VecScatterEnd        100 1.0 6.2196e-02 3.0 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00  0  0  0  0  0  22  0  0  0  0     0       0      0 0.00e+00    0 0.00e+00  0
VecCUDACopyTo        100 1.0 1.0850e-02 2.3 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00  0  0  0  0  0   5  0  0  0  0     0       0    100 1.02e+02    0 0.00e+00  0
VecCopyFromSome      100 1.0 1.0263e-01 1.2 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00  0  0  0  0  0  54  0  0  0  0     0       0      0 0.00e+00  100 2.69e+02  0

6 MPI ranks + 6 GPUs + CUDA-aware SF
MatMult              100 1.0 1.1112e-01 1.0 9.66e+09 1.1 2.8e+03 2.2e+05 0.0e+00  1 99 97 18  0 100100100100  0 509496   3133521   0 0.00e+00    0 0.00e+00 100
VecScatterBegin      100 1.0 7.9461e-02 1.1 0.00e+00 0.0 2.8e+03 2.2e+05 0.0e+00  1  0 97 18  0  70  0100100  0     0       0      0 0.00e+00    0 0.00e+00  0
VecScatterEnd        100 1.0 2.2805e-02 1.5 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00  0  0  0  0  0  17  0  0  0  0     0       0      0 0.00e+00    0 0.00e+00  0

24 MPI ranks + 6 GPUs + regular SF
MatMult              100 1.0 1.1094e-01 1.0 2.63e+09 1.2 1.9e+04 5.9e+04 0.0e+00  1 99 97 25  0 100100100100  0 510337   951558  100 4.61e+01  100 6.72e+01 100
VecScatterBegin      100 1.0 4.8966e-02 1.8 0.00e+00 0.0 1.9e+04 5.9e+04 0.0e+00  0  0 97 25  0  34  0100100  0     0       0      0 0.00e+00  100 6.72e+01  0
VecScatterEnd        100 1.0 7.2969e-02 4.9 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00  1  0  0  0  0  42  0  0  0  0     0       0      0 0.00e+00    0 0.00e+00  0
VecCUDACopyTo        100 1.0 4.4487e-03 1.8 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00  0  0  0  0  0   3  0  0  0  0     0       0    100 4.61e+01    0 0.00e+00  0
VecCopyFromSome      100 1.0 4.3315e-02 1.9 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00  0  0  0  0  0  29  0  0  0  0     0       0      0 0.00e+00  100 6.72e+01  0

24 MPI ranks + 6 GPUs + CUDA-aware SF
MatMult              100 1.0 1.4597e-01 1.2 2.63e+09 1.2 1.9e+04 5.9e+04 0.0e+00  1 99 97 25  0 100100100100  0 387864   973391    0 0.00e+00    0 0.00e+00 100
VecScatterBegin      100 1.0 6.4899e-02 2.9 0.00e+00 0.0 1.9e+04 5.9e+04 0.0e+00  1  0 97 25  0  35  0100100  0     0       0      0 0.00e+00    0 0.00e+00  0
VecScatterEnd        100 1.0 1.1179e-01 4.1 0.00e+00 0.0 0.0e+00 0.0e+00 0.0e+00  1  0  0  0  0  48  0  0  0  0     0       0      0 0.00e+00    0 0.00e+00  0


--Junchao Zhang

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