Develop Algorithms

Develop MATLAB^® algorithms that can be deployed to NVIDIA^® boards

The MATLAB Coder™ Support Package for NVIDIA Jetson™ and NVIDIA DRIVE^® Platforms relies on the MATLAB Coder base product to generate optimized C/C++ code and the GPU Coder™ product to generate optimized CUDA^® code. The generated code can then be deployed to NVIDIA platforms targeting either the ARM^® CPUs or the CUDA capable GPUs on these platforms.

Topics

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.

Featured Examples

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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