Getting Started

About JupyterHub

Jupyter is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. As such, Jupyterhub, an extension of Jupyter Notebook, is a valuable tool which

  • enhances accessibility of high performance computational resources beyond the command line interface

  • encourages collaboration across departments  

  • greatly improves the time from coding to results

Deployed is a JupyterHub environment utilizing Jupyterlab, not the classic Jupyter Notebook. For more on Jupyterlab, see here

Please note that all jobs submitted through this framework have a time limit of 8 hours. 

Supported Kernels

  • python 3.9.16

  • python 3.6.6

  • python 2.7.1

  • R 3.5.1 (howto)

  • pangeo

  • Custom Kernels (howto)

Using Jupyterhub to Access ARCC General Purpose Cluster

Note: More information on the general-purpose cluster can be found here. You must have a research account in order to use this resource and using a VPN if off-campus. Please contact askIT@albany.edu if you need an account.

  1. Navigate to https://jupyterlab.its.albany.edu and log in with your NetID and password. 

  2. Now, you will be prompted to spawn a server. Several options are available for users to select. Please select the appropriate profile from the drop-down menu, and do not request more resources than you need. All jobs have a time limit of 8 hours.

  3. This will spawn Jupyterlab in your /network/rit/home/ directory. You will not be able to navigate to other parts of the file system, unless they are linked to your home directory. However, your code can access any network path that you have permission to access. Note that by default, you will not see the R kernel. Please follow these instructions to enable it




  4. Happy coding!