Using TIDE

TIDE, being part of the National Research Platform Nautilus hyper-cluster, offers several ways to take advantage of the advanced resources. The TIDE project offers a managed JupyterHub instance with several pre-built software containers with many common packages common to artificial intelligence, machine learning, and data science. Additional container images can be added or created by the TIDE support team.

For more advanced use cases, containers can be executed on the TIDE resources as jobs.


JupyterHub offers web-based access to TIDE resources from any web browser. When launching your JupyterHub server you select from a list of pre-configured software containers as well as what resources you need, including graphical processing units (GPUs).

Getting started:

  1. Use the TIDE Support Request form to request access to the TIDE JupyterHub instance
  2. Once access is granted, review the Quickstart guide on the TIDE GitHub documentation site
  3. Review of the list of software container images available, if you have any questions, submit a TIDE Support Request
  4. Access the TIDE JupyterHub using your campus credentials and launch your server


For longer running or complex jobs, containers can be executed in “namespaces” as pods/jobs. Namespaces are a way to organize users, jobs, and other resources.

For assistance creating a namespace submit a TIDE Support Request and the team will reach out to gather more details.