Anaconda

Dask for Performance: How to measure and scale Python applications for Dask

Catch up on the latest with Dask—a flexible library for parallel computing

Learn best practices for performance profiling and tuning for parallel computations in this Anaconda webinar. Lead Dask Developer Matthew Rocklin will use Dask to cover:

  • How to profile, visualize, and tune normal Python code
  • Why common approaches break down when we transition to parallel and distributed computing
  • How Dask's diagnostics, feedback, and visual dashboards can help us understand and improve performance at scale
  • Common performance pitfalls, and how to address them effectively

Meet Our Speaker

  • Matthew Rocklin
    Software Engineer, Anaconda

    Matthew is an open source software developer focusing on efficient computation and parallel computing, primarily within the Python ecosystem. He has contributed to many of the PyData libraries and today works on Dask, a framework for parallel computing.

    Matthew holds a PhD in computer science from the University of Chicago, where he focused on numerical linear algebra, task scheduling, and computer algebra. He lives in Brooklyn, NY.

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