Videos

Generate CUDA code from MATLAB code for NVIDIA GPUs.
GPU Coder generates optimized CUDA code from MATLAB code for deep learning, embedded vision, and autonomous systems. See GPU Coder in action with a ray tracing example.
See how to integrate neural networks for deep learning applications into Simulink and use the approach to leverage deep learning-based algorithms in control applications such as lane departure systems.
Learn how you can use GPU Coder hardware support package for NVIDIA GPUs to prototype, verify, and deploy your deep learning models and algorithms in MATLAB for embedded vision, autonomous driving applications on NVIDIA GPUs like the NVIDIA Drive.
Walk through a real-time object detection example using YOLO v2 in MATLAB. Generate optimized CUDA code and verify it using a mex file that runs at about 80 fps on a test file. Deploy the generated...
See an example of a DAG network for semantic segmentation. Using the cnncodegen function in GPU Coder, generate CUDA code and build it into a MEX function that runs 6x faster than in MATLAB.
Generate CUDA code from a trained deep neural network in MATLAB and leverage the NVIDIA TensorRT library for inference on NVIDIA GPUs using a pedestrian detection application as an example.
Generate code from a trained neural network in MATLAB for Intel processors and see how the network for pedestrian detection runs on an Intel Xeon E5 v3 processor using MKL-DNN library at about 30 fps.
See how you can generate code from a trained deep neural network in MATLAB for ARM processors showing pedestrian detection on a Raspberry Pi 3 at 6 fps.
Generate code from a trained neural network in MATLAB for Intel processors and see how the network for pedestrian detection runs on an Intel Xeon E5 v3 processor using MKL-DNN library at about 30 fps.
Learn how you can use MATLAB to build your deep learning and computer vision applications and then deploy them on the NVIDIA Jetson AGX Xavier to detect defective products in a machine vision context.
Use GPU Coder to generate CUDA code from a fog rectification algorithm written in MATLAB.
Learn how to use GPU Coder to deploy a deep neural network in MATLAB to a NVIDIA Jetson board.
See an example of a real-time object detection algorithm using a deep learning neural network based on YOLO architecture. Using cnncodegen function, you can generate CUDA code and integrate it into a bigger application.
Learn how GPU Coder can be used to deploy deep learning algorithms from MATLAB to embedded NVIDIA GPUs, and how the deployed code can be used with the Robot Operating System (ROS).
Learn how you can use GPU Coder hardware support package for NVIDIA GPUs to prototype, verify, and deploy your deep learning models and algorithms in MATLAB for embedded vision, autonomous driving applications on NVIDIA GPUs like the NVIDIA Drive.