Parallelizing Computation with Dask Delayed and Futures

This class module focuses on using the Dask scheduler to empower custom parallel computation. Dask Delayed and Futures represent lightweight mechanisms for building and running custom task graphs, while staying within traditional Python coding patterns. This combination – regular Python code with a powerful distributed scheduler – enables all kinds of industry or discipline-specific workloads to be parallelized for fast, large-scale computation.

Learn Ideas and Gain Skills

Duration: one day

Prerequisites

Topics

Introduction

Building and Running Graphs with Delayed

Running and Managing Work with Futures

Review and Q&A