Treffer: Integrating interactive performance analysis in Jupyter Notebooks for parallel programming education

Title:
Integrating interactive performance analysis in Jupyter Notebooks for parallel programming education
Publisher Information:
Zenodo
Publication Year:
2024
Collection:
Zenodo
Document Type:
E-Ressource software
Language:
English
DOI:
10.5281/zenodo.10573107
Rights:
Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number:
edsbas.3A22928D
Database:
BASE

Weitere Informationen

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.