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Open OnDemand

Open OnDemand (OOD) is platform for accessing the clusters that only requires a web browser. This web-portal provides a shell, file browser, and graphical interface for certain apps (like Jupyter or MATLAB).


If you access Open OnDemand installed on YCRC clusters from off campus, you will need to first connect to the Yale VPN.

Open OnDemand is available on the following clusters using your NetID credentials (CAS login).

Cluster OOD site

The above four URLs are also called cluster OOD URLs. They are available to any user with a research account (also called a lab account) on the clusters. Your research account is the same as your NetID.

Course Open OnDemand Web Portals

Courses on the clusters have their own course-specific OOD URLs, also called course OOD web portals. Through the course OOD URLs, students will sign in with their NetID but work under their student account. The course URLs all follow the same naming convention: More information about course OODs can be found at academic support.


If you only have a student account, but try to sign in through the cluster OOD URL, you will get an error in the browser:

Error -- can't find user for cpsc424_test
Run 'nginx_stage --help' to see a full list of available command line options.
Instead, use the course OOD URL.

The Dashboard

On login you will see the OOD dashboard.


Along the top are pull-down menus for various Apps, including File Managers, Job Composer, a Shell, a list of Interactive Apps, etc.

File Browser


The file browser is a graphical interface to manage, upload, and download files from the clusters. You can use the built-in file editor to view and edit files from your browser without having to download and upload scripts.

You can also drag-and-drop to download and upload files and directories, and move files between directories using this interface.

Customize Favorite Paths

Users are allowed to customize favorite paths in the file manager. Using the scripts below to add, remove, and list customized paths:

When you run ood_add_path from a shell command line, it will prompt you to add one path at a time, until you type 'n' to discontinue. All the paths added by you will be shown in the OOD pull-down menu for the file manager, as well as the left pane when the file manager is opened.

ood_remove_path allows you to remove any of the paths added by you and ood_list_path will list all the paths added by you.

After you have customized the path configuration from a shell, go to the OOD dashbaord and click Develop->Restart Web Server on the top menu bar to make the change effective immediately.


You can launch a traditional command-line interface to the cluster using the Shell pull-down menu. This opens a terminal in a web-browser that you can use in the exact same way as when logging into the cluster via SSH.

This is a convenient way to access the clusters when you don't have access to an ssh client or do not have your ssh keys.

Interactive Apps

We have deployed a selection of common graphical programs as Interactive Apps on Open OneDemand. Currently, we have apps for Remote Desktop, MATLAB, Mathematica, RStudio Desktop, RStudio Server, and Jupyter Notebook, etc.

Remote Desktop

Occasionally, it is helpful to use a graphical interface to explore data or run certain programs. In the past your options were to use VNC or X11 forwarding. These tools can be complex to setup or suffer from reduced performance. The Remote Desktop app from OOD simplifies the configuration of a VNC desktop session on a compute node. The MATLAB, Mathematica, and RStudio Desktop Apps are special versions of this app. To get started choose Remote Desktop (or another desktop app) from the Interactive Apps menu on the dashboard.

Use the form to request resources and decide what partition your job should run on (use interactive or your lab's partition).


Once you launch the job, you will be presented with a notification that your job has been queued. Depending on the resources requested, you may need to wait for a bit. When the job starts you will see the option to launch the Remote Desktop:


Note you can share a view only link for your session if you would like to share your screen. After you click on Launch Remote Desktop, a standard desktop interface will open in a new tab.


In some browsers, you may have to use a special text box to copy and paste from the Remote Desktop App. Click the arrow on the left side of your window for a menu, then click the clipboard icon to get access to your Remote Desktop's clipboard.



One of the most common uses of Open OnDemand is the Jupyter interface for Python and R. You can choose either Jupyter Notebook or Jupyter Lab. By default, this app will try to launch Jupyter Notebook, unless the Start JupyterLab checkbox is selected.


Make sure that you chose the right Conda environment for your from the drop-down menu. If you have not yet set one up, follow our instructions on how to create a new one. After specifying the required resources (number of CPUs/GPUs, amount of RAM, etc.), you can submit the job. When it launches you can open the standard Jupyter interface where you can start working with notebooks.


The ycrc_default conda environment will be automatically built when you select it for the first time from Jupyter. You can also build your own Jupyter and make it available to OOD:

module load miniconda
conda create -n env_name jupyter jupyter-lab
ycrc_conda_env.list build  

Once created, ycrc_default will not be updated by OOD automatically. It must be updated by the user manually. To update ycrc_default, run the following command from a shell command line:

module load miniconda
conda update -n  ycrc_default jupyter jupyter-lab

RStudio Server

Change User R Package Path

To change the default path where packages installed by the user are stored, you need to add the following line of code in your $HOME/.bashrc:

export R_LIBS_USER=path_to_your_local_r_packages

Configure the Graphic Device

When you plot in a RStudio session, you may encounter the following error:

Error in RStudioGD() : 
  Shadow graphics device error: r error 4 (R code execution error)
In addition: Warning message:
In grDevices:::png("/tmp/RtmpcRxRaB/4v3450e3627g4432fa27f516348657267.png",  :
  unable to open connection to X11 display ''

To fix the problem, you need to configure RStudio Server to use Cairo as the graphic device backend. To do so, first click Tools from the top menu bar on the RStudio Server GUI, and then select Global options from the pull down menu. An option window will be opened. In the window, click general on the left panel and then click Graphics on the right. Choose Cairo from the backend list.

Once done, it sets Cairo as the default drawing device. You only need to configure the device once unless you have cleaned up your RStudio configuration files.


Troubleshoot OOD

An OOD session is started and then completed immediately

  1. Check if your quota is full
  2. Reset your .bashrc and .bash_profile to their original contents (you can backup the startup files before resetting them. Add the changes back one at a time to see if one or more of the changes would affect OOD from starting properly)
  3. Remove the default module collection file $HOME/.lmod.d/default.cluster-rhel7 (cluster is one of the following: grace, farnam, ruddle, milgram)

Remote Desktop (or MATLAB, Mathematica, etc) cannot be started properly

  1. Make sure there is no initialization left by conda init in your .bashrc. Clean it with
    sed -i.bak -ne '/# >>> conda init/,/# <<< conda init/!p' ~/.bashrc
  2. Run dbus-launch and make sure you see the following output:
    [pl543@grace1 ~]$ which dbus-launch

Jupyter cannot be started properly

  1. If you are trying to launch jupyter-notebook, make sure it is available in your jupyter conda environment:
    (ycrc_default)[pl543@grace1 ~]$ which jupyter-notebook
  2. If you are trying to launch jupyter-lab, make sure it is available in your jupyter conda environment:
    (ycrc_default)[pl543@grace1 ~]$ which jupyter-lab

RStudio with Conda R

If you see NOT_FOUND in "Conda R Environment", it means your Conda R environment has not been properly installed. You may need to reinstall your Conda R environment and make sure r-base r-essentials are both included.

Last update: February 28, 2022