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Jupyter is a literate computing software ecosystem for working with digital documents called notebooks that can contain executable code, equations, visualizations, interactive interfaces, text, and metadata. Use Jupyter at NERSC to:

  • Perform exploratory data analysis and visualization of data stored at NERSC
  • Guide machine learning through distributed training, hyperparameter optimization, model validation, prediction, and inference
  • Manage workflows involving simulation and data analysis on GPU or CPU compute nodes
  • ... or something else we haven't thought of yet!

To access Jupyter at NERSC, simply visit with your web browser, authenticate, and launch a notebook server.

Jupyter Documentation

The Jupyter documentation is organized into a few sections.

  • How-To: Step-by-step instructions to help you manage your Jupyter experience at NERSC.
  • Reference: Helpful facts and definitions related to how Jupyter is deployed at NERSC.
  • Background: Context provided to expand user understanding about the service.

Getting Help with Jupyter

If you run into problems with Jupyter at NERSC or just have questions about how to use it, please use the NERSC Help Portal to open a ticket and we will get back to you as soon as possible. In that case, before opening your ticket you may want to examine your Jupyter logs.

You may also find the #jupyter channel on the NERSC User Group Slack to be a useful resource where fellow users share knowledge, experiences, and advice. But again, to get help from NERSC staff, use the Help Portal.