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titleAccessing the Research Cluster via SSH

First, login via SSH to the “researchcluster-login.ucsd.edu" Linux server login node using your UC San Diego Active Directory (AD) username (with ‘@researchcluster-login.ucsd.edu’) and password.  After logging in, you will be in a login node for the Research Cluster and should not perform any computation in the login node.

Login step-by-step guidance:

  1. Open command line interface - known as the 'Terminal' for MacOS and 'Command Prompt' for Windows.

  2. Enter command ‘ssh ADusername@researchcluster-login.ucsd.edu'.

    1. If the researchcluster-login.ucsd.edu login node is currently down/unavailable, you may temporarily TEMPORARILY use the “dsmlp-login.ucsd.edu” login node instead. The dsmlp-login.ucsd.edu login node is primarily reserved intended for instructional classwork class work use by students as its first priority, so it’s recommended to always use the researchcluster-login.ucsd.edu for research work. Student involved in research projects should login to the relevant login node depending on the intended work (class work versus research work).

You may be asked a question after entering your username. Select 'yes’ to continue connecting.

  1. Enter your password. Note: Your password will not display as you enter it.

  2. A successful login will display your last login information. For example, ‘Last login: Thu Aug 3 10:25:19 2023 from 137.110.14.162’. Note that you are now in the Login Node. 

IMPORTANT: DO NOT RUN JOBS IN THE LOGIN NODE. ! Jobs must only be run in a launched container. Follow the guidance in the next section (Launching a Container), before running your compute jobs. 

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titleAccessing the Research Cluster via the datahub

  1. Login page: https://datahub.ucsd.edu .

    • Enter UCSD email address and AD password. You will be sent a push to confirm via Duo.

  2. Select the your chosen notebook environment. 

    • Research Cluster users will have a choice of multiple environments to select.

    • If joining a PI/lab specific environment, your may only see the name of your PI/lab’s environment.

    • The ‘public’ folder will include storage that is shared and where datasets can be stored for all to access.

  3. Next, you’ll be directed to your environment and see the Jupyter Notebook interface.

  4. Click ‘New’ and select the kernel you wills to start up.

  5. When done using the datahub, select ‘logout’ to terminate kernels and end session.

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