Deploy MATLAB and Simulink to NVIDIA GPUs

NVIDIA GPUs are the hardware of choice for many applications including AI, embedded vision, and radar and signal processing algorithms. MATLAB is the ideal environment for exploring, developing, and prototyping algorithms. In this seminar, we will learn how to generate CUDA code directly from MATLAB and Simulink to run on NVIDIA GPUs using GPU Coder. We'll walk you through the workflow that starts with designing and simulating various applications, including defective product detection and lane/vehicle detection, in MATLAB and Simulink running on the CPU, testing it on the same machine using an RTX GPU, then deploying it onto a Jetson AGX Orin. Learn how to access peripherals from the Jetson platform for use in MATLAB/Simulink and with the generated code. Related resources: - White Paper: Generating CUDA Code from MATLAB: Accelerating Embedded Vision and Deep Learning Algorithms on GPUs: https://bit.ly/2VaHN3P - Deploy MATLAB and Simulink to NVIDIA GPUs: http://bit.ly/46RpXdH Chapters: 00:00 Introduction 00:34 Example: Automated Optical Inspection 06:13 What is GPU Coder? 13:23 Example: Using GPU Coder for Automated Optical Inspection 21:00 Example: Using GPU Coder Performance Analyzer 28:19 Deep Learning Workflow 32:34 Key Take-Aways -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2025 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.