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If you are making use of Jupyter notebook to write your python scripts then you first need to make sure you export the .py file in Jupyter and then copy it onto the cluster
Also ensure job is copied to /mnt/lustre/users/YOURUSERNAME or subdirectories therein
Running Tensorflow on CPU nodes
To test a job on a compute node first get onto an interactive node with the following:
qsub -I -P YOURPROGRAMME(E.G. CSCI1234) -q smp -l select=1:ncpus=24
Once on an interactive node (cnodeNNNN) you need to load up the appropriate modules:
module purge module load chpc/python/3.6.1_gcc-6.3.0
Then
cd /mnt/lustre/users/YOURUSERNAME or where ever you placed your .py file
Finally run
python nameofyourfile.py
Running Tensorflow on GPU nodes
As with CPU version you can test your python jobs on an interactive node:
qsub -I -P YOURPROGRAMME(E.G. CSCI1234) -q gpu_1 -l select=1:ncpus=10:ngpus=1
Once on an interactive node (gpuNNNN) you need to load up appropriate modules:
module purge module load chpc/cuda/10.0 module load chpc/python/anaconda/3
Then
cd /mnt/lustre/users/YOURUSERNAME or where ever you placed your .py file
When running on a single GPU you need to include the following in your .py file to ensure that not all the CPU's on the node get consumed, thereby resulting in your job being killed by the scheduler
session_conf = tf.ConfigProto(intra_op_parallelism_threads=10,inter_op_parallelism_threads=10)
sess = tf.Session(config=session_conf)
Finally run
python nameofyourfile.py
This page will be updated once I have written some scripts that can be used to submit jobs via the PBS scheduler Dr Krishna Govender
