The best way to learn is by doing! And to help you get started, we have assembled a series of tutorials and instructional materials featuring the latest developer innovations. Please see below for details.
Sign Up for Upcoming Webinars
Register for our exclusive NVIDIA DRIVE developer webinar series designed for automotive developers who are part of the NVIDIA DRIVE Developer Program for DRIVE AGX.
In each hour-long session, NVIDIA experts will dive into the details of various aspects of the end-to-end AV computational pipeline and will be available for live Q&A. There are two sessions of each webinar to accommodate the global timezone, please use the multi-registration to sign up for
Attendees will hear updates on our key initiatives for autonomous driving including:
- Introducing NVIDIA DRIVE OS, the Functional Safety Operating System for Autonomous Vehicles
Wednesday, June 24, 2020, 9:00 AM PDT | 6:00 PM PDT
- Building AI-Enabled AV Applications with NVIDIA DRIVE Software
Wednesday, June 30, 2020, 9:00 AM PDT | 6:00 PM PDT
- Perception and Mapping Architecture for Autonomous Vehicles
Wednesday, July 08, 2020, 9:00 AM PDT | 6:00 PM PDT
- Planning and Control Architecture and Implementation for Autonomous Vehicles
Wednesday, July 22, 2020, 9:00 AM PDT | 6:00 PM PDT
- Introducing DRIVE Infrastructure – The Complete Datacenter Infrastructure to Build Autonomous Vehicles
Wednesday, August 05, 2020, 9:00 AM PDT | 6:00 PM PDT
- Developing Intelligent In-Cabin Experience Using DRIVE IX
Wednesday, August 19, 2020, 9:00 AM PDT | 6:00 PM PDT
NVIDIA DRIVE AGX is an open, scalable architecture for autonomous driving capabilities, from NCAP through robotaxi. NVIDIA has developed a unique suite of SoC, GPU, and Smart Network computational and acceleration options for flexible autonomous vehicle development. This session provides details on our latest SoC, GPU, and Smart Network products and how they can be used in a vehicle computer architecture. We also go over DRIVE AGX Hyperion sensor solutions for both passenger cars and commercial trucks.
In this webinar, we covered the steps to perform inference on a pretrained network with DriveWorks. We first review DriveWorks basics before exploring the DriveWorks DNN APIs and tools to convert, optimize and run inference. Finally we walk through sample code that demonstrates how to integrate your DNN into your software pipeline.
In this webinar we introduce CUDA cores, threads, blocks, gird, and stream and the TensorRT workflow. We also cover CUDA memory management and TensorRT optimization, and how you can deploy optimized deep learning networks using TensorRT samples on NVIDIA DRIVE AGX.
The second installment of this webinar series explains how to extend TensorRT with custom operations, running custom layers through TensorRT using the plugin interface. For the fastest implementation of custom layers, it is necessary to use the same GPU by building CUDA kernels on which the optimized engine will run. We then cover TensorRT plugins and how to adapt CUDA kernel as a part of the TensorRT plugin for DNN model optimization with a sample application.
Concurrent execution of multiple GPU inferencing tasks provides potential performance optimization when compared to its serialized counterpart. As a real-world use case, we implement a multi-network inference pipeline for object detection and lane segmentation. In building this application, we show how to achieve kernel concurrency using multiple CUDA Streams and CUDA Graphs. We then introduce how to use NVIDIA NSight Systems to profile the application, showing the performance gains from implementing concurrency.
This webinar covers the steps to develop camera image processing software on the DriveWorks SDK. Using this platform, developers can implement a range of capabilities seamlessly and with high performance. This webinar includes DriveWorks image basics, low-level Computer Vision modules, and Feature Tracking and DNN samples.
This webinar covers how to implement and use the sensor plugins for different sensor types such as radar, lidar, and camera. Such plugins will make it possible for developers to bring new sensors into the DriveWorks SAL and to implement the transport and protocol layers necessary to communicate with the sensor.
Peek under the hood of NVIDIA DRIVE Software with our latest video series.
Deep Learning Institute (DLI)
In this workshop, you will learn how to design, train, and deploy deep neural networks for autonomous vehicles using the NVIDIA DRIVE™ AGX Development platform. Learn how to:
- Integrate sensor input using the DriveWorks software stack
- Train a semantic segmentation neural network
- Optimize, validate, and deploy a trained neural network using TensorRT
Upon completion, participants will be able to create and optimize perception components for autonomous vehicles using NVIDIA DRIVE™.
- Prerequisites: Experience with CNNs
- Frameworks: TensorFlow, DIGITS, TensorRT
- Languages: English, Chinese, Japanese
In this 6 months nanodegree program, you will build the skills and learn the techniques used by self-driving car teams at the most advanced technology companies in the world. Learn how to:
- Apply computer vision and deep learning to automotive problems
- Use sensor fusion to perceive the environment
- Program Udacity’s real self-driving car
- Prerequisites: Experience with Python and C++
- Languages: English