Learning Outcomes

Note

• Learn the basics of Dask.

• Learn how to use distributed Dask in an HPC machine.

• Learn how to use machine learning algorithms in Dask.

In this tutorial, we will learn how to use Dask to scale Python code for parallel and distributed computing. Dask is a flexible parallel computing library that enables efficient processing of large datasets and complex workflows on a single machine or a cluster. We will cover the basics of Dask’s features, building and optimizing task graphs, and integrating with libraries like NumPy and pandas. By the end, you’ll understand how to use Dask to enhance your code’s scalability and performance.