Infrastructure
C025 Hub Server
You can use our workstation in C025 lab if you need computing facilities such as GPU, but the available resouces are limited with 24 cores of CPU, 40GB RAM, and 2x Nvidia 3090 with 24 GB GPU memory each. However, if you need more resources, please request access to the university HPC cluster.
We also provide a JupyterHub server on the workstation so that you do not have to setup the environment.
Hub Server
The address of the JupyterHub server is https://10.20.118.78:32025 and LDAP is used for the login.
Multiple environments can be provided and is described in here. You can choose the one that meets your needs or PR to the aforementioned repository if you need to update the libraries. We can, of course, provide more environment options as per request.
Deep Learning env with Tensorflow and Pytorch is default environment and contains several deep learning libraries defined in gpu-notebook. The GPUs are accessible by all authorized users and there is no individual GPU resouce allocation.
Access
In order to get access to the hub, we need to add your LDAP username.
Hint
Admins can add new users by going to admin page https://10.20.118.78:32025/hub/admin.
Within the university network:
You can access the hub directly from the university network.
Remote access
University VPN
Follow this instruction to setup VPN in your local machine. Once you are connected to the university VPN, you can open the Hub address.
SSH tunnel
If you do not want to use VPN, you can port forward from your FB02 account to C025 workstation
# replace account2s with your FBUID ssh -L 32025:10.20.118.78:32025 account2s@home.inf.h-brs.de
Then, open browser and go to https://localhost:32025.
Note
SSH access to the workstation is only possible with ssh key, so if you need it, please send us your ssh key.