New Environment at High Performance Computing for Instructors

Tandon Online,
Workshop / Training
For NYU Community

High Performance Computing helping process Big Data

In-person and online workshop

The NYU HPC team maintains and provides access to a centralized JupyterHub environment to support courses. 

If you are an instructor or TA who considers using the centrally provided jupyterHub environment in the Spring (or future) semester you should plan to attend. 

The presentation will cover the features of the newly deployed environment on the Google Cloud Platform (GCP), which include:

- R and Python kernels (Jupyter Notebook, JupyterLab, RStudio)
- Instructors control many parameters of student environment in a self-service mode.
- Parameters include: RAM, persistent storage usage, GPU usage, environment, auto download of files from private GitHub repositories
- NBGrader extension of JupyterHub, which allows to distribute and grade assignments automatically
- Instructors have an option (and actually expected) to use conda environments for packages installation (both R and Python)
- Instructors control a list of users allowed to log in (and may make their class open for all temporally).

Register Here

Submit the course in-take form before coming to the meeting.

Join us to learn about all the features and discuss your course requirements.