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Goals:

  • Walk through a options within a Jupyter Notebook session

Initial Screen Navigation and Options

Upon connecting, you are presented with a simple Jupyter Notebook screen and just a few options:

  • Drop down menu bar along the top

  • Active work area:

    • When you into the cluster for the first time, this area will display the default, which initially shows 2 tabs:

      • File Browser

      • Run Manager

 

Drop-Down Menu Bar

  • File: actions related to files and folders

  • View: actions that alter the appearance of Jupyter Notebook

  • Settings: common settings

  • Help: a list of Jupyter Notebook and kernel help links

Notebookdropdown.png

Active Work Area

Whatever you’re currently working on

  • Shown below the drop down menu

  • Usually this is a Jupyter Notebook

  • At default start, shows file and run tabs

NotebookActiveWorkArea.png

Opening a New Blank Notebook

From the Dropdown:

File->New->Notebook

From the Right side of the File Management Tab:

New->Notebook

Kernels

A Jupyter kernel is the computational engine behind the code execution in Jupyter notebooks.

Most users think of this as the “compiler” or programming language used when running code cells.
The Kernel empowers you to execute code in different programming languages like Python, R, or Julia or others and instantly view the outcomes within the notebook interface.

After opening a new notebook, you will be prompted to select a kernel

  • If you have never created a kernel to use, you will only see a list of default Jupyter kernels available on the cluster

  • You may check the box to start with the preferred kernel every time you open a notebook

Default Kernels on ARCC HPC Resources include:

  • Python Kernels

  • R Kernels

HPC-wide kernels are titled by packages installed and available when launched

Users can also create user-defined kernels from conda environments (Covered in a subsequent module. See Creating Jupyter Kernels from Conda Environments)

Starting Jupyter from OnDemand

 

Dive into Jupyter Labs

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