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 (GPU Coder)

Introduction to GPU accelerated computing.

Code Generation by Using the GPU Coder App (GPU Coder)

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

Code Generation Using the Command Line Interface (GPU Coder)

Generate CUDA C 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 and Run Sobel Edge Detection with I/O on NVIDIA Jetson Nano

Deploy Sobel edge detection that uses Raspberry Pi Camera Module V2 and display on the NVIDIA Jetson Nano Hardware using the GPU Coder™ Support Package for NVIDIA® GPUs. In the example Sobel Edge Detection on NVIDIA Jetson Nano using Raspberry Pi Camera Module V2, we have seen accessing the Raspberry Pi Camera Module V2 on NVIDIA Jetson Nano hardware using the GPU Coder Support Package for NVIDIA GPUs. In the current example, we will generate code for accessing I/O (camera and display) to deploy on the NVIDIA Jetson Nano hardware. We will consider the same Sobel edge algorithm for showing this capability.

Open Script
Sobel Edge Detection on NVIDIA Jetson Nano using Raspberry Pi Camera Module V2

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 right into the MATLAB® environment for processing. In this example you will learn how to develop a Sobel edge detection algorithm by using this capability.

Open Script
Semantic Segmentation on NVIDIA DRIVE

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 on Semantic Segmentation, see Code Generation for Semantic Segmentation Network.

Open Script
GPU Coder Support Package for NVIDIA GPUs Documentation
Support
Generating CUDA Code from MATLAB: Accelerating Embedded Vision and Deep Learning Algorithms on GPUs

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

Download white paper