Développer des algorithmes
MATLAB Coder™ Support Package for NVIDIA Jetson™ and NVIDIA DRIVE® Platforms s’appuie sur le produit de base MATLAB Coder pour générer du code C/C++ optimisé et sur le produit GPU Coder™ pour générer du code CUDA® optimisé. Le code généré peut ensuite être déployé sur les plateformes NVIDIA en ciblant soit leurs CPU ARM®, soit leurs GPU compatibles CUDA.
Rubriques
- GPU Programming Paradigm (GPU Coder)
Introduction to GPU accelerated computing.
- Generate Code by Using the GPU Coder App (GPU Coder)
Generate CUDA code from MATLAB code by using the GPU Coder app.
- Generate Code Using the Command Line Interface (GPU Coder)
Generate CUDA code from MATLAB code by using the
codegencommand. - MATLAB Language Features Support for GPU Coder (GPU Coder)
Use the MATLAB language capabilities that GPU Coder supports.
- Supported Functions (GPU Coder)
Alphabetical list of MATLAB and toolbox functions that GPU Coder supports.
- Kernel Creation (GPU Coder)
Algorithm structures and patterns that create CUDA GPU kernels
- Code Generation for Deep Learning Networks by Using cuDNN (GPU Coder)
Generate code for pretrained convolutional neural networks by using the cuDNN library.
- Code Generation for Deep Learning Networks by Using TensorRT (GPU Coder)
Generate code for pretrained convolutional neural networks by using the TensorRT library.
Sélection d՚exemples
Deploy and Run Sobel Edge Detection with I/O on NVIDIA Jetson Nano
Generate code for accessing I/O peripherals (camera and display) and perform processing on the NVIDIA Jetson Nano hardware.
Sobel Edge Detection on NVIDIA Jetson Nano Using Raspberry Pi Camera Module V2
Capture and process images from a Raspberry Pi® Camera Module V2 connected to the NVIDIA® Jetson™ Nano. The MATLAB® Coder™ Support Package for NVIDIA Jetson and NVIDIA DRIVE® Platforms allows you to capture images from the Camera Module V2 and bring them into the MATLAB environment for processing. In this example you learn how to develop a Sobel edge detection algorithm by using this capability.
Semantic Segmentation on NVIDIA DRIVE
Generate and deploy a CUDA® executable for an image segmentation application that uses deep learning. It uses the MATLAB® Coder™ Support Package for NVIDIA® Jetson™ and NVIDIA DRIVE™ Platforms to deploy the executable on the NVIDIA DRIVE platform. This example performs code generation on the host computer and builds the generated code on the target platform by using remote build capability of the support package. For more information, see Code Generation for Semantic Segmentation Network (GPU Coder).
