Added arguments for job script

This commit is contained in:
Martin Lilleeng Sætra 2022-04-07 13:52:16 +02:00
parent bf8dc33b28
commit 353056d5b1
3 changed files with 20 additions and 20 deletions

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@ -6,7 +6,7 @@
#SBATCH --account=nn9882k #SBATCH --account=nn9882k
# #
# Wall clock limit: # Wall clock limit:
#SBATCH --time=00:20:00 #SBATCH --time=00:02:00
# #
# NOTE: See https://documentation.sigma2.no/jobs/projects_accounting.html when adjusting the values below # NOTE: See https://documentation.sigma2.no/jobs/projects_accounting.html when adjusting the values below
# #
@ -28,7 +28,7 @@
# source /cluster/bin/jobsetup # source /cluster/bin/jobsetup
module restore system # instead of 'module purge' rather set module environment to the system default module restore system # instead of 'module purge' rather set module environment to the system default
module load CUDA/10.2.89 module load CUDA/11.4.1
# It is also recommended to to list loaded modules, for easier debugging: # It is also recommended to to list loaded modules, for easier debugging:
module list module list
@ -41,7 +41,7 @@ mkdir $SCRATCH/ShallowWaterGPU
cp -r . $SCRATCH/ShallowWaterGPU cp -r . $SCRATCH/ShallowWaterGPU
## Make sure the results are copied back to the submit directory (see Work Directory below): ## Make sure the results are copied back to the submit directory (see Work Directory below):
# chkfile MyResultFile # chkfile MyResultFileq
# chkfile is replaced by 'savefile' on Saga # chkfile is replaced by 'savefile' on Saga
savefile "$SCRATCH/ShallowWaterGPU/*.log" savefile "$SCRATCH/ShallowWaterGPU/*.log"
savefile "$SCRATCH/ShallowWaterGPU/*.nc" savefile "$SCRATCH/ShallowWaterGPU/*.nc"

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@ -6,26 +6,26 @@
#SBATCH --account=nn9882k #SBATCH --account=nn9882k
# #
# Wall clock limit: # Wall clock limit:
#SBATCH --time=10:00:00 #SBATCH --time=00:10:00
#
# 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 # 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 # device(s) to use. It will have values '0', '1' or '0,1' corresponding to
# /dev/nvidia0, /dev/nvidia1 or both, respectively. # /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: # 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 --qos=devel
#SBATCH --nodes=1 --ntasks-per-node=1
## Set up job environment: (this is done automatically behind the scenes) ## Set up job environment: (this is done automatically behind the scenes)
## (make sure to comment '#' or remove the following line 'source ...') ## (make sure to comment '#' or remove the following line 'source ...')
# source /cluster/bin/jobsetup # source /cluster/bin/jobsetup
module restore system # instead of 'module purge' rather set module environment to the system default module restore system # instead of 'module purge' rather set module environment to the system default
module load CUDA/10.2.89 module load CUDA/11.4.1
# It is also recommended to to list loaded modules, for easier debugging: # It is also recommended to to list loaded modules, for easier debugging:
module list module list
@ -47,5 +47,5 @@ savefile "$SCRATCH/ShallowWaterGPU/*.json"
## Do some work: ## Do some work:
cd $SCRATCH/ShallowWaterGPU cd $SCRATCH/ShallowWaterGPU
srun $HOME/.conda/envs/ShallowWaterGPU_HPC/bin/python3 --version srun $HOME/.conda/envs/ShallowWaterGPU_HPC/bin/python3 --version
srun $HOME/.conda/envs/ShallowWaterGPU_HPC/bin/python3 mpiTesting.py -nx 1024 -ny 1024 --profile srun $HOME/.conda/envs/ShallowWaterGPU_HPC/bin/python3 mpiTesting.py -nx $NX -ny $NY --profile

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@ -1,13 +1,13 @@
#!/bin/bash #!/bin/bash
# one node: 1-4 tasks/GPUs # one node: 1-4 GPUs
sbatch --partition=accel --gres=gpu:1 --nodes=1 --ntasks-per-node=1 saga_strong_scaling_benchmark.job sbatch --nodes=1 --gpus-per-node=1 --ntasks-per-node=1 --export=ALL,NX=1024,NY=1024 saga_strong_scaling_benchmark.job
sbatch --partition=accel --gres=gpu:2 --nodes=1 --ntasks-per-node=2 saga_strong_scaling_benchmark.job sbatch --nodes=1 --gpus-per-node=2 --ntasks-per-node=2 --export=ALL,NX=1024,NY=512 saga_strong_scaling_benchmark.job
sbatch --partition=accel --gres=gpu:3 --nodes=1 --ntasks-per-node=3 saga_strong_scaling_benchmark.job sbatch --nodes=1 --gpus-per-node=3 --ntasks-per-node=3 --export=ALL,NX=1024,NY=341 saga_strong_scaling_benchmark.job
sbatch --partition=accel --gres=gpu:4 --nodes=1 --ntasks-per-node=4 saga_strong_scaling_benchmark.job sbatch --nodes=1 --gpus-per-node=4 --ntasks-per-node=4 --export=ALL,NX=512,NY=512 saga_strong_scaling_benchmark.job
# 2-4 nodes: 4 tasks/GPUs per node # 2-4 nodes: 1 GPUs per node
sbatch --partition=accel --gres=gpu:4 --nodes=2 --ntasks-per-node=4 saga_strong_scaling_benchmark.job sbatch --nodes=2 --gpus-per-node=1 --ntasks-per-node=1 --export=ALL,NX=1024,NY=512 saga_strong_scaling_benchmark.job
sbatch --partition=accel --gres=gpu:4 --nodes=3 --ntasks-per-node=4 saga_strong_scaling_benchmark.job sbatch --nodes=3 --gpus-per-node=1 --ntasks-per-node=1 --export=ALL,NX=1024,NY=341 saga_strong_scaling_benchmark.job
sbatch --partition=accel --gres=gpu:4 --nodes=4 --ntasks-per-node=4 saga_strong_scaling_benchmark.job sbatch --nodes=4 --gpus-per-node=1 --ntasks-per-node=1 --export=ALL,NX=512,NY=512 saga_strong_scaling_benchmark.job