I just joined this community, and this is my first message here. I am a second-year student studying SE in Serbia. I’ve set up JupyterHub from my Ubuntu server, which runs on 8GPUS. I am looking to restrict and manage GPU resources for the users of JupyterHub.Some schemes would look like this:
|- user1: 2 usable GPUs
|- user2: 3 usable GPUs
|- user3: 4 usable GPUs
|- user4: 1 usable GPU
I looked through documentation from links( such as:
-Setting up GPU Data Science Environments for Hackathons | by Jacob Tomlinson | RAPIDS AI | Medium
Trust me, my first three pages of google are purple ), and I could not find the particular thing that is suitable for me and working. This is what I have so far, and with sudo tljh-config show:
users: admin: - skynet allowed: - good-user_1 - marko limits: memory: 4G marko: CUDA_VISIBLE_DEVICES: 0,1,2 https: enabled: true user_environment: default_app: jupyterhub marko: CUDA_VISIBLE_DEVICES: 0,1,2
Have you experienced a similar problem, and what will you advise me to do? Is it even possible to manage resources with the JupyterHub interface?
Thank you in advance for your time.
I am looking forward to hearing from you!