Develop Algorithms

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

The GPU Coder™ Support Package for NVIDIA GPUs relies on the GPU Coder base product to generate optimized CUDA^® code that can be deployed to NVIDIA GPU platforms.

Topics

GPU Programming Paradigm

Introduction to GPU accelerated computing.

Code Generation by Using the GPU Coder App

Generate CUDA C code from MATLAB code by using the GPU Coder app.

Code Generation Using the Command Line Interface

Generate CUDA C code from MATLAB code by using the codegen command.

MATLAB Language Features Support for GPU Coder

Use the MATLAB language capabilities that GPU Coder supports.

Supported Functions

Alphabetical list of MATLAB and toolbox functions that GPU Coder supports.

Kernel Creation

Algorithm structures and patterns that create CUDA GPU kernels

Code Generation for Deep Learning Networks by Using cuDNN

Generate code for pretrained convolutional neural networks by using the cuDNN library.

Code Generation for Deep Learning Networks by Using TensorRT

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 using the GPU Coder™ Support Package for NVIDIA® GPUs. 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 using the GPU Coder™ Support Package for NVIDIA GPUs. The GPU Coder Support Package for NVIDIA GPUs 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 GPU Coder™ Support Package for NVIDIA® GPUs 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.

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Develop Algorithms

Topics

Featured Examples

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

Sobel Edge Detection on NVIDIA Jetson Nano Using Raspberry Pi Camera Module V2

Semantic Segmentation on NVIDIA DRIVE

GPU Coder Support Package for NVIDIA GPUs Documentation

Support

Generating CUDA Code from MATLAB: Accelerating Embedded Vision and Deep Learning Algorithms on GPUs