NVIDIA DRIVE® Infrastructure encompasses the complete data center hardware, software, and workflows needed to develop autonomous driving technology—from raw data collection through validation. Whether in the cloud or on-premises, NVIDIA provides the end-to-end building blocks for neural network development, training, and validation, plus testing in simulation.
High-performance, energy-efficient AI computing is the foundation for the development, deployment, and operation of autonomous vehicles. It enables efficient processing of data and rapid AI model training–ensuring real-time decision-making for safe and reliable automated driving.
DGX Cloud provides high-performance computing at scale, letting automotive companies quickly develop AI algorithms critical to AV development. The cloud-based infrastructure also powers large-scale replay, enabling OEMs to test their AI against previously collected ground-truth data.
DGX SuperPOD™ is a state-of-the-art AI computing infrastructure comprised of multiple DGX servers to deliver remarkable performance. This enables OEMs to train and optimize deep learning models faster and more efficiently–reducing the time it takes to develop safe autonomous driving systems.
NVIDIA AI Enterprise is the software layer of the NVIDIA AI platform and includes access to hundreds of AV frameworks. These includeTensorFlow, PyTorch, and NVIDIA® CUDA-X™, letting AV companies create, test, train, and deploy complex AI algorithms.
NVIDIA LaunchPad provides free access to NVIDIA AI running in the cloud. Speed the development and deployment of modern, data-driven applications and quickly test and prototype your entire AI workflow.
It’s impossible to fully test AVs for each driving scenario in the real world. NVIDIA DRIVE Sim™, built on NVIDIA Omniverse™, accelerates AV development and increases safety with end-to-end simulation where virtual vehicle fleets can drive millions of miles in a broad range of scenarios—from routine driving to rare or even dangerous situations. DRIVE Sim also taps into the capabilities of NVIDIA Omniverse Replicator to generate physically based, synthetic ground-truth data to address the limitations of real-world data collection and tailor scenarios to specific development needs.
Omniverse Cloud is a platform-as-a-service that provides a full-stack cloud environment—enabling OEMs to test and validate autonomous vehicles in a physically based virtual environment.
NVIDIA OVX™ Server is designed to run DRIVE Sim with the complex sensor architectures necessary for autonomous driving. OVX combines high-performance compute and GPU-accelerated graphics with high-speed storage access, low-latency networking, and precision timing. This delivers the performance required for scalable software-in-the-loop (SIL) AV simulation.
As a core extension of NVIDIA Omniverse, Replicator generates 3D synthetic data that covers gaps where data can't be collected, labeled, or efficiently scaled in the real world. This can significantly reduce AV development time and cost.
Hear how leaders in the AV industry are approaching this challenge to deploy safe self-driving vehicles for transportation and delivery.
Breakthroughs by NVIDIA Research demonstrate the power of Omniverse digital twins to reconstruct real-world scenarios in simulation.
Learn how DRIVE Sim provides the digital twin environment to train, test, and validate automated driving functions> You’ll also see how NVIDIA Omniverse enables the development of factory digital twins, in-vehicle experiences, and car configurators.
Gain insights from NVIDIA's AV training and testing efforts on NVIDIA DGX SuperPOD, including AI infrastructure at scale, overcoming data management challenges, and ML Ops.
Learn how to use NVIDIA DRIVE Replicator for generating physically accurate synthetic datasets along with ground-truth labels for training autonomous vehicle perception models.
This session covers the latest advancements in DRIVE Sim that combine real-world data with AI reconstruction techniques to achieve both the realism and scale needed for AV development.
Hear how NVIDIA is developing autonomous vehicles and training neural networks to let AVs perceive and react to their environments.
Learn now how developers can test a virtually limitless number of scenarios, repeatably and at scale, with high-fidelity, physically based simulation to expedite the development of AVs.
Find out how you can start developing AI-powered autonomous vehicles.