NVIDIA OVX Purpose-built for creating and operating Omniverse applications at data center-scale. Contact Us
Image courtesy of Prof. Tang, Princeton Plasma Physics Laboratory, US DIII-D NVIDIA Extends Omniverse to Scientific Computing Omniverse now connects to leading scientific computing visualization software and supports new batch rendering workloads on systems powered by NVIDIA A100 and H100 Tensor Core GPUs. Read the Press Release
Lockheed Martin, NVIDIA to Help Speed Climate Data to Researchers The U.S. National Oceanic and Atmospheric Administration (NOAA) selects Lockheed Martin and NVIDIA to build a system to output complex visualizations from the latest climate data to researchers in 10 minutes or less with NVIDIA Omniverse. Read Blog
Oregon State University to Receive NVIDIA DGX SuperPOD and OVX SuperPOD Clusters The Jen-Hsun and Lori Huang Collaborative Innovation Complex will house a supercomputer powerful enough to train the largest AI models and perform complex digital twin simulations. Read the Blog
Announcing Omniverse Cloud Design, publish, and experience metaverse applications from anywhere. Read the Press Release Visit Webpage
NVIDIA and Siemens Expand Partnership to Build Autonomous Factories Siemens is using the new NVIDIA IGX platform with NVIDIA Metropolis to provide advanced perception for safe and secure industrial-edge AI. Read the Blog Visit Webpage
Siemens and NVIDIA Partner to Build Industrial Metaverse Connecting the Siemens Xcelerator ecosystem with NVIDIA Omniverse’s AI-enabled, physically accurate simulation engine enables a new era of industrial automation. Learn More
The NVIDIA OVX platform will provide the performance and scale needed for Omniverse simulations that will allow us to more quickly and accurately predict the intensity and progress of wildfires and optimize response efforts to mitigate their damaging impacts. — Justin Taylor | VP of Artificial Intelligence | Lockheed Martin
In our current project, NVIDIA OVX will provide the scale, performance and compute capabilities that we need to generate data for intensive machine learning development and operate these highly complex simulations and scenarios. — Annika Hundertmark | Head of Railway Digitization | Deutsche Bahn