Integrating interactive performance analysis in Jupyter Notebooks for parallel programming education

This repository enables performance analysis of parallel C++ programs in a JupyterLab environment using the xeus-cling notebook kernel.
It features a JupyterLab extension (./jupyterlab_performance_display) that provides a graphical user interface for running experiments.
The extension uses a C++ API (./performance) to run performance analysis tools like Score-P, Scalasca and Cube and creates visualizations.

The data collected and evaluated during the study are stored in a jamovi project file.