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Merge branch 'master' of github.com:setmar/ShallowWaterGPU

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This commit is contained in:
Martin Lilleeng Sætra 2022-01-24 19:58:12 +01:00
commit 5b6e145d80
4 changed files with 17 additions and 13 deletions
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2
README.md
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@ -21,6 +21,8 @@ Example job script:
dgx-2-test.job
Submit:
module use /cm/shared/ex3-modules/latest/modulefiles # Latest ex3-modules
module load slurm/20.02.7 # To load slurm module
sbatch dgx-2-test.job
### PPI 4 x P100 (VPN necessary)

15
saga-dev.job
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@ -3,22 +3,23 @@
#SBATCH --job-name=ShallowWaterGPUScalingDev
#
# Project:
#SBATCH --account=nn9550k
#SBATCH --account=nn9882k
#
# Wall clock limit:
#SBATCH --time=01:00:00
#SBATCH --time=00:20:00
#
# NOTE: See https://documentation.sigma2.no/jobs/projects_accounting.html when adjusting the values below
#
# Ask for 1 GPU (max is 2)
# Note: The environment variable CUDA_VISIBLE_DEVICES will show which GPU
# device(s) to use. It will have values '0', '1' or '0,1' corresponding to
# /dev/nvidia0, /dev/nvidia1 or both, respectively.
#SBATCH --partition=accel --gres=gpu:1
#SBATCH --partition=accel
#
# Max memory usage per task (core) - increasing this will cost more core hours:
#SBATCH --mem-per-cpu=16G
#SBATCH --mem-per-cpu=3800M
#
# Number of tasks:
#SBATCH --nodes=1 --ntasks-per-node=1
#SBATCH --nodes=1 --gpus-per-node=1 --ntasks-per-node=1
#
#SBATCH --qos=devel
@ -49,5 +50,5 @@ savefile "$SCRATCH/ShallowWaterGPU/*.json"
## Do some work:
cd $SCRATCH/ShallowWaterGPU
srun $HOME/.conda/envs/ShallowWaterGPU_HPC/bin/python3 --version
srun $HOME/.conda/envs/ShallowWaterGPU_HPC/bin/python3 mpiTesting.py -nx 8192 -ny 8192 --profile
srun $HOME/.conda/envs/ShallowWaterGPU_HPC/bin/python3 mpiTesting.py -nx 1024 -ny 1024 --profile

11
saga-test.job
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@ -3,22 +3,23 @@
#SBATCH --job-name=ShallowWaterGPUStrongScaling
#
# Project:
#SBATCH --account=nn9550k
#SBATCH --account=nn9882k
#
# Wall clock limit:
#SBATCH --time=24:00:00
#
# Ask for 1 GPU (max is 2)
# NOTE: See https://documentation.sigma2.no/jobs/projects_accounting.html when adjusting the values below
#
# Note: The environment variable CUDA_VISIBLE_DEVICES will show which GPU
# device(s) to use. It will have values '0', '1' or '0,1' corresponding to
# /dev/nvidia0, /dev/nvidia1 or both, respectively.
#SBATCH --partition=accel --gres=gpu:1
#SBATCH --partition=accel
#
# Max memory usage per task (core) - increasing this will cost more core hours:
#SBATCH --mem-per-cpu=16G
#SBATCH --mem-per-cpu=3800M
#
# Number of tasks:
#SBATCH --nodes=1 --ntasks-per-node=1
#SBATCH --nodes=1 --gpus-per-node=1 --ntasks-per-node=1
## Set up job environment: (this is done automatically behind the scenes)
## (make sure to comment '#' or remove the following line 'source ...')

2
saga_strong_scaling_benchmark.job
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@ -3,7 +3,7 @@
#SBATCH --job-name=ShallowWaterGPUStrongScaling
#
# Project:
#SBATCH --account=nn9550k
#SBATCH --account=nn9882k
#
# Wall clock limit:
#SBATCH --time=10:00:00