The UChicago JupyterLab

underconstruction

Table of contents

Login to JupyterLab at UChicago

How to launch JupyterLab at UChicago

Once you login, click "Services" on the top menu bar, then choose "JupyterLab". You will need to make some choices in order to configure your JupyterLab notebook:

 1. Provide a notebook name that has no whitespace, using 30 characters or less from the set [a-zA-Z0-9._-] to name your notebook.
 4. You can request 1 to 16 CPU cores.
 5. You can request 1 to 32 GB of memory.
 6. You can request 0 to 7 GPU instances.
 7. You can select a GPU model based on its memory size.
 8. If you request a GPU, please make sure the GPU is available, by clicking on the icon next to GPU memory.
 9. You can give the notebook a duration of 1 to 168 hours.
10. You can choose any Docker image from the dropdown.

Choose a Docker image

ml-platform:latest: NVidia GPU and ROOT support This image has most of the ML packages (Tensorflow, Keras, ScikitLearn, etc.) preinstalled, and a small tutorial with code examples in /ML_platform_tests/tutorial.

ml-platform:conda: With full Anaconda through Micromamba, keep reading to learn how to use it.

ml-platform:julia: With Julia programming languge

ml-platform:lava: With Intel Lava neuromorphic computing framework

ml-platform:centos7-experimental 

code

Using ATLAS environment at JupyterLab UChicago

command text

Images

Getting help

Please use the following e-mail addresses to get help. The division below is not strict. Questions will be routed to appropriate staff members.
1. Use atlas-us-UChicago-acf@cern.ch for ATLAS specific questions and requestions, including ATLAS software related issues.
2. Use unix-admin@UChicago.stanford.edu for all other questions.

For software additions and upgrades please contact ivukotic@uchicago.edu.