servers - neuralinterfacinglab/LabManual GitHub Wiki
Servers
Currently, we have one GPU server
FHMLFYSLNX001 living in UNS50 F1.150a
Rules
- Make sure to monitor resource usage and be considerate
htop
can be used to monitor CPU and RAM usagenvidia-smi -l 1
shows GPU usagedu -hs ./*/
shows the size of all folders in our/project
drive. Make sure clean up regularly.
Connecting
- Simply connect via
ssh
using your normal UM credentials. The server is running on 3389. screen
allows you to start a session that you can reconnect to, should the connection be lost, or you want to shutdown your computer.
Getting data on the server
Data for your projects should be stored in /projects
.
An administrator (i.e. Christian) will create a folder for you.
Copy data to the server with your favorite scp client (e.g. WinSCP)
Using python on the server
You need to install your own python environments, for example with miniconda
VS Code remote
Install the Remote - SSH extension
Connect via SSH (bottom left corner) - Work on VSCode as normal
CUDA:
I want to use those cool GPUs, how do I do this? Run the following commands once:
echo "export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}" >> ~/.bashrc
echo "export LD_LIBRARY_PATH=/usr/local/cuda-12.2/lib64\
${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}" >> ~/.bashrc
Freesurfer
Run the following commands once:
echo "FREESURFER_HOME=/usr/local/freesurfer" >> ~/.bashrc
echo 'source $FREESURFER_HOME/SetUpFreeSurfer.sh' >> ~/.bashrc
The patient folder is set to /project/imaging/subjects
Graphical User Interface
Wait! All of this is in consoles. I want a User Interface.
- Using Windows
Remote Desktop Connection
, which requires a separate User and Password, you can log in and work remotely. Beware, this is a lot slower.