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In this video, Matt Rocklin explains static Dask Performance Reports and shows how to create and share static HTML files that capture performance information. What is Dask? Dask is a free and open-source library for parallel computing in Python. Dask is a community project maintained by developers and organizations. What are Dask Performance Reports? Often when benchmarking and/or profiling, users may want to record a particular computation or even a full workflow. Dask can save the bokeh dashboards as static HTML plots including the task stream, worker profiles, bandwidths, etc. Dask has the ability to generate static Dask Performance Reports and save the results to a standalone HTML file. These performance reports are useful for later inspection since they can be viewed after your computation is finished and your cluster is no longer running. Understanding the performance of a distributed computation can be difficult. This is due in part to the many components of a distributed computer that may impact performance such as compute time, memory bandwidth, network bandwidth, disk bandwidth, scheduler overhead, and serialization costs. This difficulty is compounded because the information about these costs is spread among many machines and so there is no central place to collect data to identify performance issues. Fortunately, Dask collects a variety of diagnostic information during execution. It does this both to provide performance feedback to users, but also for its own internal scheduling decisions. The primary place to observe this feedback is the diagnostic dashboard. Share your feedback with us in the comments and let us know: - Did you find the video helpful? - Do you have specific questions about Dask Performance Reports? Learn more at dask.org KEY MOMENTS 00:00:00 Intro 00:00:24 Performance Report Context Manager 00:01:23 Static HTML File 00:01:47 Sharing

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