Love Python but wish it could crunch through your data a little faster? Dask makes it easy to scale familiar Python workflows beyond a single core, helping you tackle larger datasets and speed up analyses without completely rewriting your code.
In this Quick Byte* session, we'll introduce the basics of Dask and show you how to use it on CURC resources. You'll learn how to parallelize workloads with Dask Arrays and DataFrames, launch Dask clusters from Open OnDemand Jupyter sessions, and use the Dask Dashboard to monitor and optimize your computations. We'll wrap up with a demonstration of running a parallel workflow on Alpine and share practical tips for deciding when Dask is the right tool for the job.
*What is a Quick Byte? A Quick Byte is a 20-30 minute session intended to provide essential information about a specific topic. You can expect to leave a 'Quick Byte' with the information you need to apply a tool, service, or concept.
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