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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 simultaneously. 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.

While VS Code supports normal Microsoft account, UNSW SSO is NOT supported. To void confusion, here we cover GitHub only.

#!/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

A GitHub account is required for authentication to access the established Remote Tunnels.

$ 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/

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/

#!/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]

$ 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

The compilation will not fully completed but there are enough CUDA binaries can be used for testing.

# 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