Introduction: This workshop will discuss how to use Jupyter Notebooks and Jupyter Labs on ARCC HPC clusters and introduce a series of best practices.
This tutorial is available for download as a PDF here.
Course Goals:
Introduce what Jupyter is and why it’s useful
Identify the difference between Jupyter Lab and Jupyter Notebooks and when to use one tool is better than the otherover another
Demonstrate the Jupyter service within OnDemand across a variety of available languages and kernels
Demonstrate how Provide the steps to convert an existing Conda environment into a kernel that can be used within a Jupyter session
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Notebooks vs Labs
Creating a Shared Library of R Packages: Demonstrate how to use an R library to create a shared set of R packages.
Using R and RStudio within OnDemand: Detail the process of using R and RStudio via the OnDemand service.
Using an R Conda Environment with RStudio: Detail how to use an R Conda Environment within RStudio.
Create an R Kernel for a Jupyter Notebook: Detail how to update an R Conda environment so it can be used as a kernel within ARCC’s Jupyter service.
Parallel R: Introduction: Introduction some high-level aspects of using R in parallel relating to the cluster.
Using R/RStudio on the Cluster: Summary: Summarize the concepts covered across the workshop.
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