[petsc-users] CUDA error trying to run a job with two mpi processes and 1 GPU

Vanella, Marcos (Fed) marcos.vanella at nist.gov
Mon Aug 21 14:38:00 CDT 2023


Ok thanks Junchao, so is GPU 0 actually allocating memory for the 8 MPI processes meshes but only working on 2 of them?
It says in the script it has allocated 2.4GB
Best,
Marcos
________________________________
From: Junchao Zhang <junchao.zhang at gmail.com>
Sent: Monday, August 21, 2023 3:29 PM
To: Vanella, Marcos (Fed) <marcos.vanella at nist.gov>
Cc: PETSc users list <petsc-users at mcs.anl.gov>; Guan, Collin X. (Fed) <collin.guan at nist.gov>
Subject: Re: [petsc-users] CUDA error trying to run a job with two mpi processes and 1 GPU

Hi, Macros,
  If you look at the PIDs of the nvidia-smi output, you will only find 8 unique PIDs, which is expected since you allocated 8 MPI ranks per node.
  The duplicate PIDs are usually for threads spawned by the MPI runtime (for example, progress threads in MPI implementation).   So your job script and output are all good.

  Thanks.

On Mon, Aug 21, 2023 at 2:00 PM Vanella, Marcos (Fed) <marcos.vanella at nist.gov<mailto:marcos.vanella at nist.gov>> wrote:
Hi Junchao, something I'm noting related to running with cuda enabled linear solvers (CG+HYPRE, CG+GAMG) is that for multi cpu-multi gpu calculations, the GPU 0 in the node is taking what seems to be all sub-matrices corresponding to all the MPI processes in the node. This is the result of the nvidia-smi command on a node with 8 MPI processes (each advancing the same number of unknowns in the calculation) and 4 GPU V100s:

Mon Aug 21 14:36:07 2023
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.54.03              Driver Version: 535.54.03    CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  Tesla V100-SXM2-16GB           On  | 00000004:04:00.0 Off |                    0 |
| N/A   34C    P0              63W / 300W |   2488MiB / 16384MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   1  Tesla V100-SXM2-16GB           On  | 00000004:05:00.0 Off |                    0 |
| N/A   38C    P0              56W / 300W |    638MiB / 16384MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   2  Tesla V100-SXM2-16GB           On  | 00000035:03:00.0 Off |                    0 |
| N/A   35C    P0              52W / 300W |    638MiB / 16384MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   3  Tesla V100-SXM2-16GB           On  | 00000035:04:00.0 Off |                    0 |
| N/A   38C    P0              53W / 300W |    638MiB / 16384MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|    0   N/A  N/A    214626      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      318MiB |
|    0   N/A  N/A    214627      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      308MiB |
|    0   N/A  N/A    214628      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      308MiB |
|    0   N/A  N/A    214629      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      308MiB |
|    0   N/A  N/A    214630      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      318MiB |
|    0   N/A  N/A    214631      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      308MiB |
|    0   N/A  N/A    214632      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      308MiB |
|    0   N/A  N/A    214633      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      308MiB |
|    1   N/A  N/A    214627      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      318MiB |
|    1   N/A  N/A    214631      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      318MiB |
|    2   N/A  N/A    214628      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      318MiB |
|    2   N/A  N/A    214632      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      318MiB |
|    3   N/A  N/A    214629      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      318MiB |
|    3   N/A  N/A    214633      C   ...d/ompi_gnu_linux/fds_ompi_gnu_linux      318MiB |
+---------------------------------------------------------------------------------------+


You can see that GPU 0 is connected to all 8 MPI Processes, each taking about 300MB on it, whereas GPUs 1,2 and 3 are working with 2 MPI Processes. I'm wondering if this is expected or there are some changes I need to do on my submission script/runtime parameters.
This is the script in this case (2 nodes, 8 MPI processes/node, 4 GPU/node):

#!/bin/bash
# ../../Utilities/Scripts/qfds.sh -p 2  -T db -d test.fds
#SBATCH -J test
#SBATCH -e /home/mnv/Firemodels_fork/fds/Issues/PETSc/test.err
#SBATCH -o /home/mnv/Firemodels_fork/fds/Issues/PETSc/test.log
#SBATCH --partition=gpu
#SBATCH --ntasks=16
#SBATCH --ntasks-per-node=8
#SBATCH --cpus-per-task=1
#SBATCH --nodes=2
#SBATCH --time=01:00:00
#SBATCH --gres=gpu:4

export OMP_NUM_THREADS=1
# modules
module load cuda/11.7
module load gcc/11.2.1/toolset
module load openmpi/4.1.4/gcc-11.2.1-cuda-11.7

cd /home/mnv/Firemodels_fork/fds/Issues/PETSc

srun -N 2 -n 16 /home/mnv/Firemodels_fork/fds/Build/ompi_gnu_linux/fds_ompi_gnu_linux test.fds -pc_type gamg -mat_type aijcusparse -vec_type cuda

Thank you for the advice,
Marcos



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