Difference between revisions of "K-Scale Cluster"

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     IdentityFile ~/.ssh/id_rsa
 
     IdentityFile ~/.ssh/id_rsa
 
</syntaxhighlight>
 
</syntaxhighlight>
 
You need to restart <code>ssh</code> to get it working.
 
  
 
After setting this up, you can use the command <code>ssh cluster</code> to directly connect.
 
After setting this up, you can use the command <code>ssh cluster</code> to directly connect.
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=== Notes ===
 
=== Notes ===
  
 +
* You may need to restart <code>ssh</code> to get it working.
 
* You may be sharing your part of the cluster with other users. If so, it is a good idea to avoid using all the GPUs. If you're training models in PyTorch, you can do this using the <code>CUDA_VISIBLE_DEVICES</code> command.
 
* You may be sharing your part of the cluster with other users. If so, it is a good idea to avoid using all the GPUs. If you're training models in PyTorch, you can do this using the <code>CUDA_VISIBLE_DEVICES</code> command.
 
* You should avoid storing data files and model checkpoints to your root directory. Instead, use the <code>/ephemeral</code> directory. Your home directory should come with a symlink to a subdirectory which you have write access to.
 
* You should avoid storing data files and model checkpoints to your root directory. Instead, use the <code>/ephemeral</code> directory. Your home directory should come with a symlink to a subdirectory which you have write access to.

Revision as of 21:11, 27 April 2024

The K-Scale Labs cluster is a shared cluster for robotics research. This page contains notes on how to access the cluster.

Onboarding

To get onboarded, you should send us the public key that you want to use and maybe your preferred username.

After being onboarded, you should receive the following information:

  • Your user ID (for this example, we'll use stompy)
  • The jumphost ID (for this example, we'll use 127.0.0.1)
  • The cluster ID (for this example, we'll use 127.0.0.2)

To connect, you should be able to use the following command:

ssh -o ProxyCommand="ssh -i ~/.ssh/id_rsa -W %h:%p stompy@127.0.0.1" stompy@127.0.0.2 -i ~/.ssh/id_rsa

Note that ~/.ssh/id_rsa should point to your private key file.

Alternatively, you can add the following to your SSH config file, which should allow you to connect directly, Use your favorite editor to open the ssh config file (normally located at ~/.ssh/config for Ubuntu) and paste the text:

Host jumphost
    User stompy
    Hostname 127.0.0.1
    IdentityFile ~/.ssh/id_rsa

Host cluster
    User stompy
    Hostname 127.0.0.2
    ProxyJump jumphost
    IdentityFile ~/.ssh/id_rsa

After setting this up, you can use the command ssh cluster to directly connect.

You can also access via VS Code. Tutorial of using ssh in VS Code is here.

Please inform us if you have any issues!

Notes

  • You may need to restart ssh to get it working.
  • You may be sharing your part of the cluster with other users. If so, it is a good idea to avoid using all the GPUs. If you're training models in PyTorch, you can do this using the CUDA_VISIBLE_DEVICES command.
  • You should avoid storing data files and model checkpoints to your root directory. Instead, use the /ephemeral directory. Your home directory should come with a symlink to a subdirectory which you have write access to.