알고리즘 개발하기

NVIDIA^® 보드에 배포할 수 있는 MATLAB^® 알고리즘 개발

MATLAB Coder™ Support Package for NVIDIA Jetson™ and NVIDIA DRIVE^® Platforms는 MATLAB Coder 기본 제품을 사용하여 최적화된 C/C++ 코드를 생성하고 GPU Coder™ 제품을 사용하여 최적화된 CUDA^® 코드를 생성합니다. 생성된 코드는 이러한 플랫폼의 ARM^® CPU 또는 CUDA 지원 GPU를 타깃으로 하는 NVIDIA 플랫폼에 배포할 수 있습니다.

도움말 항목

GPU Programming Paradigm (GPU Coder)
Introduction to GPU accelerated computing.
Code Generation by Using the GPU Coder App (GPU Coder)
Generate CUDA code from MATLAB code by using the GPU Coder app.
Code Generation Using the Command Line Interface (GPU Coder)
Generate CUDA code from MATLAB code by using the codegen command.
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.

추천 예제

Deploy and Run Sobel Edge Detection with I/O on NVIDIA Jetson Nano

Deploy Sobel edge detection application that uses a Raspberry Pi Camera Module V2 and displays the edge detected output on the NVIDIA® Jetson™ Nano Hardware. The Sobel Edge Detection on NVIDIA Jetson Nano Using Raspberry Pi Camera Module V2 example showed how to capture image frames from the Raspberry Pi Camera Module V2 on an NVIDIA Jetson Nano hardware and process them in the MATLAB® environment. This example shows how to generate code for accessing I/O peripherals (camera and display) and perform processing on the NVIDIA Jetson Nano hardware.

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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.

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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).

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