Integrating interactive performance analysis in Jupyter Notebooks for parallel programming education
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.
interactive programming, high performance computing, parallel programming, jupyter, hpc, mpi, performance analysis, jupyter notebook, jupyterlab
Jupyter Notebook
interactive programming, high performance computing, parallel programming, jupyter, hpc, mpi, performance analysis, jupyter notebook, jupyterlab
Jupyter Notebook
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