Learn how you can solve computationally and data intensive problems using multicore processors, GPUs, and compute clusters.
https://github.com/mathworks/parallel-computing-hands-on-workshop
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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
Zitieren als
Sam Marshalik (2026). Parallel Computing Hands-on Workshop (https://github.com/mathworks/parallel-computing-hands-on-workshop/releases/tag/v1.0), GitHub. Abgerufen .
Allgemeine Informationen
- Version 1.0 (11,9 MB)
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Lizenz auf GitHub anzeigen
Kompatibilität der MATLAB-Version
- Kompatibel mit R2016b und späteren Versionen
Plattform-Kompatibilität
- Windows
- macOS
- Linux
| Version | Veröffentlicht | Versionshinweise | Action |
|---|---|---|---|
| 1.0 |
