User Management
To add users to the server, please follow the following steps:
Add username (UID) to the JupyterHub allowed list under admin tab ToDo: picture
Add username along with the requested resource to the
user-list.csv
# list of users
vim /srv/jupyterhub/users/user-list.csvUsername Node RAM CPU GPU GPU_shared Start_time End_time Staff Image muenst2s node0+node1 64 24 3 1 14.03.2023-12:00 14.04.2024-19:00 1 ghcr.io/b-it-bots/docker/gpu-notebook:11.3.1-cudnn8-runtime-ubuntu20.04+ghcr.io/digiklausur/docker-stacks/notebook-dev:latest mmuens2s node0 8 4 2 0 14.02.2023-12:00 14.02.2024-19:00 0 mmuensd2s dynamic_node 64 24 3 1 14.03.2023-12:00 14.04.2024-19:00 1 ghcr.io/b-it-bots/docker/gpu-notebook:11.3.1-cudnn8-runtime-ubuntu20.04+ghcr.io/digiklausur/docker-stacks/notebook-dev:latest
Username
: UID of the userNode
: Nodes availabe to users (options:node0
,node1
,node2
,node3
,node4
, anddynamic_node
). Sign+
indicates that the user has access to multiple nodes that are labelleda2s.cluster.gpu/node-label=<label>
, anddynamic_node
indicates that the user can be allocated dynamically (depending on the resource availability) to nodes which are labelleda2s.cluster.gpu/node-allocation=dynamic
.RAM
: Allocated RAM in GB (options:8
,16
,32
,64
)CPU
: Number of allocated CPU cores (options:8
,16
,32
)GPU
: Number of allocated GPUs (dependent on the number of GPUs available on the selected node)GPU_shared
: Set to1
to enable shared GPUStart_time
: Earliest access date for the userEnd_time
: Latest access date for the userStaff
: Set to1
if the user is a staff member with access to server configurationImage
: Image selection for the user. Sign+
indicates that the user has access to multiple images.