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General information about connecting Tel Aviv University servers is here.
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How to use SLURM is here.
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Linux servers are:
nova.cs.tau.ac.il
soul.cs.tau.ac.il
op-controller.cs.tau.ac.il
c-[001-008].cs.tau.ac.il
- Windows server is:
terminal-1.cs.tau.ac.il
- The Linux servers by default starts with tcsh. Switch to bash using the following command:
bash
- Useful software are:
gedit
matlab
python
pycharm
- op-controller.cs.tau.ac.il contains the SLURM. Sending SLURM jobs requires special permission. Useful SLURM commands are:
sinfo
squeue
srun
sbatch
- c-[001-008].cs.tau.ac.il contain directly accessible GPUs. Connect to a client cluster:
ssh c-008.cs.tau.ac.il
- View the available GPUs:
nvidia-smi
- View the users who are occupying a GPU:
ps -u -p $pid
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Create private conda environment at c-008.cs.tau.ac.il using the instructions here. All the installations must be done on the NetApp storage for example '/home/nachum/berat'
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Connect to c-008.cs.tau.ac.il and start bash
ssh c-008.cs.tau.ac.il
bash
- See the available conda virtual environments.
conda env list
- Create a virtual environment.
conda create -n venvtf tensorflow-gpu
- Deactivate the virtual environment.
conda deactivate
- See the cuda version installed on the GPU node and see the GPUs available and the nvidia-driver version.
nvcc --version
nvidia-smi
- Activate the virtual environment
conda activate venvtf
- See that tensorflow 2 is installed
conda list
- Install the other packages that you need
conda install opencv
conda install jupyterlab
conda install -c anaconda ipykernel
- Start the jupyter server in background
jupyter lab --no-browser --port=8080 &
- Open a local browser and use the following address to open the jupyter notebook
http://c-008.cs.tau.ac.il:8080
- Or open an ssh thunnel to tau server and open the jupyter client at the local host. Hence the Jupyter traffic runs through ssh.
ssh -N -L 8080:localhost:8080 berat@c-008.cs.tau.ac.il:8080
localhost:8080
- List all running programs
ps -e
ps
ps -u berat
- Kill a process by PID
kill PID