Parallel Computing Hands-on Workshop

Version 1.0 (11.9 MB) by Sam Marshalik
Learn how you can solve computationally and data intensive problems using multicore processors, GPUs, and compute clusters.
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Updated Thu, 08 Oct 2020 15:47:06 +0000

Parallel Computing Hands-On Workshop:

This hands-on workshop will introduce you to parallel computing with MATLAB® and Simulink®, so that you can solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. By working through common scenarios to parallelize MATLAB algorithms and run multiple Simulink simulations in parallel, you will gain an understanding of parallel computing with MATLAB and Simulink and learn about best practices.

Highlights:

Workshop exercises and examples will vary in difficulty from simple parallel usage concepts to more advanced techniques.

• Speeding up MATLAB applications with parallel computing
• Running multiple Simulink simulations in parallel
• GPU computing
• Offloading computations and cluster computing
• Working with large data sets

Learning Video:

Along with these exercises and examples, a video is provided to reinforce how to use parallel computing with MATLAB and Simulink. This video goes through the Parallel Computing Workshop.pdf. You can find the recorded video here:
https://www.mathworks.com/videos/parallel-computing-hands-on-workshop-1594017972362.html

Cite As

Sam Marshalik (2024). Parallel Computing Hands-on Workshop (https://github.com/mathworks/parallel-computing-hands-on-workshop/releases/tag/v1.0), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2020a
Compatible with R2016b and later releases
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.