Jupyter enables interactive supercomputing and is an alternative to accessing HPC resources via SSH. It allows different programming languages and runtimes to be used within a web-based environment.
While the frontend runs in the browser on the client, the commands are executed on the HPC systems. Jupyter therefore allows users to use resources (e.g. GPUs) which are not present on the client side, and to use software without having to install it locally. Only a web browser is required.
Jupyter can be accessed using the following URLs, depending on which hardware resource should be used:
Short description of Jupyter¶
Jupyter is a web application, central component of Jupyter is the Jupyter Notebook. It is a document, which can contain formatted text, executable code sections and (interactive) visualizations (image, sound, video, 3D views).
The Jupyter notebooks are executed in an interactive session on the compute nodes of the respective cluster. Access is via any modern web browser. Data is prepared and visualized on the server and therefore does not have to be transmitted over the network. Only the resulting text, image, sound and video data is transmitted. Starting point of a Jupyter session is the HOME directory of the user on the respective cluster.
JupyterLab is a modern user interface, within which one or more Jupyter notebooks can be opened, edited and executed. The individual notebooks can be arranged as tabs or tiled. JupyterLab is the standard user interface. Besides JupyterLab the classic notebook user interface is available, in which only one Jupyter notebook per browser tab can be opened at a time.
A Jupyter Kernel describes a separate process, in which one Jupyter Notebook is executed at a time. Different kernels are available for different programming languages or language versions.
Before a Jupyter session is started, the access authorization must be checked first. This is done via JupyterHub, where the resources are selected, for example the number of CPU cores, GPUs or the required main memory.
A detailed documentation of the Jupyter project can be found at https://jupyter.readthedocs.io.