Use MATLAB to Train on Jetson Nano: Unterschied zwischen den Versionen
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*The fundamentals of training an AI system is called deep learning. MATLAB provides a variety of helpful toolboxes, pre-trained networks and tools to process data into useful input for an AI [https://de.mathworks.com/videos/search.html?q=&fq%5B%5D=product:GC&page=1]. | *The fundamentals of training an AI system is called deep learning. MATLAB provides a variety of helpful toolboxes, pre-trained networks and tools to process data into useful input for an AI [https://de.mathworks.com/videos/search.html?q=&fq%5B%5D=product:GC&page=1]. | ||
#Gpu Coder | #Gpu Coder | ||
GPU Coder generates optimized CUDA® C++ from your MATLAB® algorithms, unlocking the parallel compute power of the Jetson GPU for real-time processing on your JetRacer and improve 40 times the performance on the jetracer [https://www.mathworks.com/help/coder/nvidia.html?utm_source=chatgpt.com][https://www.youtube.com/watch?v=emVRH4HfhQY&list=PLRcFXSK3rd79jpZLqttVDlBGrl6cYK3iS]. | |||
*Helps targeting GPUs for Automotive Applications. | *Helps targeting GPUs for Automotive Applications. | ||
=== [[Result]] === | === [[Result]] === | ||
Version vom 1. Juni 2025, 13:29 Uhr
Setup
Overview
To train the AI using MATLAB, I will write a script on MATLAB and then use GPU Coder to flash the function/model on the JetRacer. So all the debugging process will be on MATLAB.
Key Concepts
- Deep Learning with MATLAB
- The fundamentals of training an AI system is called deep learning. MATLAB provides a variety of helpful toolboxes, pre-trained networks and tools to process data into useful input for an AI [1].
- Gpu Coder
GPU Coder generates optimized CUDA® C++ from your MATLAB® algorithms, unlocking the parallel compute power of the Jetson GPU for real-time processing on your JetRacer and improve 40 times the performance on the jetracer [2][3].
- Helps targeting GPUs for Automotive Applications.