| Warning |
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The native interactive mode mechanism of the job scheduler does not work. Do NOT try commands like ‘qrsh’, ‘qlogin’. |
VS Code
| Note |
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VS Code stores data in the user home directory, which is shared across the CSE infrastructure (VLAB, HPC, etc.). Therefore, ensure that you do not run multiple instances of VS Code in different locations simultaneouslysimultaneously. If you are or have been running VS Code on VLAB or the login nodes, make sure to exit cleanly and stop all existing processes before proceeding. |
| Note |
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While VS Code supports normal Microsoft account, UNSW SSO is NOT supported. To void confusion, here we cover GitHub only. |
To establish a remote tunnel session on a compute node, submit the following job:
| Code Block |
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#!/bin/bash -l # PLEASE MAKE SURE YOU CHANGE THE FOLLOWING QSUB SETTINGS TO SUIT YOUR NEEDS # #$ -j y #$ -e $JOB_ID_$JOB_NAME.out #$ -o $JOB_ID_$JOB_NAME.out #$ -cwd #$ -N vscode-tunnel #$ -l mem=15G,jobfs=10G #$ -V # module load vscode/vscode-cli launch_tunnel |
The vscode CLI prints out the instruction in the job’s output file, like below, simply follow the link to get authenticated.
| Info |
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A GitHub account is required for authentication to access the established Remote Tunnels. |
| Code Block |
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$ cat 534_vscode-tunnel.out Loading vscode - vscode-cli spawn -ignore HUP /share/apps/noarch/vscode/vscode-cli/code tunnel * * Visual Studio Code Server * * By using the software, you agree to * the Visual Studio Code Server License Terms (https://aka.ms/vscode-server-license) and * the Microsoft Privacy Statement (https://privacy.microsoft.com/en-US/privacystatement). * ✔ How would you like to log in to Visual Studio Code? · GitHub Account To grant access to the server, please log into https://github.com/login/device and use code EFFF-CE86 Open this link in your browser https://vscode.dev/tunnel/wolfpack_zxxxxxx/import/xxxx/x/zxxxxxx/ |
Once the job prints out the URL, it is ready for connection. Open To connect, open the vscode on the local computer, and follow these steps.open the Command Palette (F1) and run the command Remote Tunnels. Follow the prompts:
For more detailed information, please checkout the Official document: Remote Tunnels extension.
GitHub Issue
It has been observed that VS Code sometimes fails to establish a session after successful authentication against GitHub (the 'Open this link' message never appears). The cause of this issue is unclear. Possible solutions include:
Logging out of GitHub and logging in again
Unregistering all tunnels that VS Code has saved via Remote Explorer (that’s right, ALL of them)
Reset VS Code
In case thing is broken, please try full reset:
qdelthe job which is running the VS CodeDelete any old processes on any other CSE systems (VLAB, lab computer etc)
Delete the corrupted user data:
rm -rf ~/.vscode*
X11 VNC
| Info |
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This process essentially uses SSH tunneling. If you're unfamiliar with SSH tunneling, this resource may be helpful: https://blog.mobatek.net/post/ssh-tunnels-and-port-forwarding/ |
A graphical interactive session can be obtained by running an x11vnc container. The session can be accessed via the web browser (or VNC client) on the user's local computer, with support for NVIDIA CUDA.
Please use the following submission script as a starting point:
| Code Block |
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#!/bin/bash -l # # PLEASE MAKE SURE YOU CHANGE THE FOLLOWING QSUB SETTINGS TO SUIT YOUR NEEDS # #$ -j y #$ -e $JOB_ID_$JOB_NAME.out #$ -o $JOB_ID_$JOB_NAME.out #$ -cwd #$ -N x11_vnc #$ -l mem=15G,jobfs=180G # adding more for GPGPU etc etc #$ -V #$ -P project_name module load vnc/x11vnc-nvidia # By default (if IMAGE_FILE_NAME is not provided), the newest cuda image is used. Other images are available at # /share/apps/sif/x11vnc/ # Just provide the image file name as the first argument ($1) start-vncserver [IMAGE_FILE_NAME] |
Submit this script via qsub. The VNC connection information will be available in the job output log and will look like this:
| Code Block |
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$ cat 295_x11_vnc.out
Loading vnc - x11vnc-nvidia
******** SSH TUNNEL INFO ********
You must setup SSH tunneling on your local computer for connecting.
For Windows:
https://blog.mobatek.net/post/ssh-tunnels-and-port-forwarding/
For Linux or macOS, sample ssh below:
ssh -L PORT:wp-delta-f03.cse.unsw.edu.au:PORT login.cse.unsw.edu.au
PORT for web browser: provided by the HTTP URL below
>>OR<<
PORT for VNC client: 59xx (see VNC viewer below)
Running: apptainer run -B /import/reed/8/z3155686 -B /scratch_local/295.1.all.q /share/apps/sif/x11vnc/12.6.1-cudnn-devel-ubuntu22.04-x11vnc.sif
*** Running /sbin/setuser ubuntu $DOCKER_CMD...
Open your web browser with URL:
http://localhost:6080/vnc.html?resize=downscale&autoconnect=1&password=wxaZpA1o
or connect your VNC viewer to localhost:5900 with password wxaZpA1o |
Once SSH tunnel is setup correctly, the interactive session can be accessed via browser, looks like:
Bind Paths and Mounts
By default, the startup script binds $HOME and $TMPDIR to the container, typically these two paths are available INSIDE the container out of the box:
/import/reed/8/zID(this is an example)/scratch_local/1563.1.all.q(this is an example)
Additional directories can be added to the container, by using env variable:
| Code Block |
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# This is required BEFORE submitting the job, or simply put it in .bashrc if it does not change often
export APPTAINER_BINDPATH="/PATH1,/PATH2" |
CUDA Samples
We can run CUDA Samples for verification purpose. Run the following INSIDE the interactive session:
| Info |
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The compilation will not fully completed but there are enough CUDA binaries can be used for testing. |
| Code Block |
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# switch to the temporary job scratch space on the compute node's local NVMe/SSD storage. cd /scratch_local/295.1.all.q git clone https://github.com/NVIDIA/cuda-samples.git cd cuda-samples make |
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