Add VSCode Remote SSH connection guide

docs/hpc/06_tools_and_software/09_vscode_remote_ssh_torch.mdx

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+# Connect VSCode to Torch
+Some users want to remotely work on Jupyter Notebooks using their Apptainer kernels. This is a tedious, error prone process.
+
+## Step 1: Configure SSH for key-based ssh login
+Generate an ssh key with ssh-keygen
+```bash
+$ ssh-keygen -t rsa -b 4096
+```
+
+Generating public/private rsa key pair.
+```bash
+Enter file in which to save the key (~/.ssh/id_rsa): ~/.ssh/torch_NetID
+```
+
+This will create two files on your local computer:
+```bash
+~/.ssh/torch_NetID
+~/.ssh/torch_NetID.pub
+```
+
+Append the public key `(~/.ssh/torch_NetID.pub)` to the Torch `~/.ssh/authorized_keys`.
+On your local computer:
+```bash
+$ cat ~/.ssh/torch_NetID.pub
+```
+
+Copy the full output and log on to Torch.
+On Torch:
+```bash
+$ mkdir -p ~/.ssh
+$ chmod 700 ~/.ssh
+$ nano ~/.ssh/authorized_keys
+```
+
+If authorized_keys already contains an HPC-managed key, do not remove or edit it. Add your custom SSH public key below the existing key, preferably under the line:
+```bash
+# Add custom SSH keys below
+```
+
+Paste the full public key from ~/.ssh/torch_NetID.pub into authorized_keys, save the file, then run:
+```bash
+$ chmod 600 ~/.ssh/authorized_keys
+```
+
+## Step 2: Configure local ssh config
+Update your `~/.ssh/config` accordingly:
+
+```bash
+Host torch
+  HostName login.torch.hpc.nyu.edu
+  User NetID
+  ForwardAgent yes
+  StrictHostKeyChecking no
+  UserKnownHostsFile /dev/null
+  LogLevel ERROR
+  IdentityFile ~/.ssh/torch_NetID
+  IdentitiesOnly yes
+  ServerAliveInterval 60
+```
+
+Please note that sometimes the IdentityFile won't work unless you use the standard id_rsa and id_rsa.pub. If the specified file doesn't work try it with id_rsa.
+
+## Step 3: Connect
+Install the VSCode Remote - SSH extension. 
+
+Configure Remote - SSH settings:
+Check off Remote.SSH: Lockfiles In Tmp
+Uncheck Remote.SSH: Use Flock
+
+Because Torch requires Microsoft device authentication during SSH login, VSCode may time out before you finish entering the device code. If this happens, search for Remote.SSH: Connect Timeout and set it to 120.
+
+Before connecting, open https://microsoft.com/devicelogin and keep it ready. In VSCode Remote Explorer, connect to the Torch login node: torch. When VSCode prompts for Microsoft device authentication, enter the code on the device login page. This may take a few attempts. VSCode may also prompt more than once during setup because it can open multiple SSH connections.
+
+After authentication, VSCode may take a while to install or start the VSCode server on Torch. If the connection fails during this step, try connecting again. Once the server is installed successfully, future connections are usually more consistent.
+
+Once connected, open a terminal in the VSCode remote session. The prompt should show that you are on a Torch login node, for example:
+```bash
+[NetID@torch-login-... ~]$
+```
+
+

docs/hpc/06_tools_and_software/10_use_jupyter_notebooks_in_vscode_on_torch.mdx

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+# Use Apptainer Jupyter Notebooks in VSCode on Torch
+
+This page builds on the general VSCode access instructions in 09_vscode_remote_ssh_torch. Before following this workflow, complete that setup and connect VSCode to the Torch login node.
+
+## Step 1: Install VSCode Jupyter support
+
+After connecting VSCode to the Torch login node, open the Extensions view in the VSCode remote window and search for Jupyter.
+
+Install or enable the Microsoft Jupyter extension in the remote SSH environment. If the extension is not already installed remotely, VSCode should show an option such as:
+
+`Install in SSH: torch`
+
+## Step 2: Start a dummy batch job and connect to the compute node
+
+After the Jupyter extension is installed or enabled, open a terminal in the VSCode remote session on a Torch login node.
+
+Interactive jobs on Torch may experience intermittent issues. Some compute nodes may work as expected, while others may not. As a workaround, submit a lightweight dummy batch job and then ssh to the allocated compute node after the job is running.
+
+For example:
+
+```bash
+sbatch -c4 -t2:00:00 --mem=4G --account=<account_name> --wrap "sleep infinity"
+```
+
+Replace `<account_name>` with the account for your project. After submitting the job, Slurm will print a job ID, for example:
+
+```bash
+Submitted batch job <job_id>
+```
+
+Once the job is running, identify the assigned compute node and connect to it from the VSCode terminal using SSH.
+Check the job status and assigned node:
+```bash
+squeue -u $USER
+```
+
+```bash
+ssh csXXX
+```
+
+After connecting, the terminal prompt should show the compute node:
+```bash
+[NetID@csXXX ~]$
+```
+
+## Step 3: Open the notebook
+
+Open the target .ipynb notebook in VSCode.
+
+## Step 4: Select the Apptainer kernel
+
+Use the notebook kernel picker to select the Apptainer kernel for the notebook.
+
+If the Apptainer kernel does not appear, confirm that the kernel is installed and visible on Torch before retrying in VSCode.