- We can access the server by using SSH:
ssh -L 8888:localhost:8888 [your_x_account]@mltgpu.flov.gu.se -p 62266
ssh tells the computer to connect remotely to the server.
-L 8888:localhost:8888 allows us to connect using jupyter notebooks, remove it if you don't want to do that.
-p 62266 tells the server to give your access through port 62266.
- Pay attention to PyTorch-GPU compatibility!
To set up a virtual environment on the server is suggested:
pip install virtualenv
python -m venv nlp # Create a virtual environment folder nlp under the current path
conda activate nlp # activate the virtual environment
pip install numpy jupyter # install necessary packages in your own virtual env
pip install torch torchvision torchaudio # install pytorch & cuda (make sure compatibility, avoid calling from external env)
conda deactivate # exit virtual env
- Check memory and current jobs in jupyter notebook:
!nvidia-smi
!ps -aux | grep python