In this tutorial, the Python package ipyparallel is introduced together with Jupyterhub notebooks. The ipyparallel package enables the development, debugging and interactive monitoring of parallel applications. It allows the quick parallelization of embarrassing parallel algorithms with just a few lines of code. In our tutorial we will focus on two use cases: The first use case demonstrates how to parallelize the analysis of a large dataset and significantly reduce the time to process the data. The second use case will explain how to speed up machine learning algorithms from scikit-learn using ipyparallel.
The materials can be download from
https://github.com/ResearchComputing/RMACC-2019-ipyparallel
