NVIDIA launches Digital Twin Platform
By MYBRANDBOOK
NVIDIA announced a digital twin platform for scientific computing that accelerates physics machine-learning models to solve million-x scale science and engineering problems thousands of times faster than previously possible.
The platform consists of the NVIDIA Modulus AI framework for developing physics-ML neural network models, and the NVIDIA Omniverse 3D virtual world simulation platform. It enables researchers to model complex systems, such as extreme weather events, with higher speed and accuracy when compared to previous AI models.
The platform can create interactive AI simulations in real time that are physics-informed to accurately reflect the real world, accelerating simulations such as computational fluid dynamics up to 10,000x faster than traditional methods for engineering simulation and design optimization workflows.
The latest release of Modulus allows data-driven training using the Fourier neural operator, a framework enabling AI to solve related partial differential equations simultaneously. It also integrates ML models with weather and climate data, such as the ERA5 dataset from the European Centre for Medium-Range Weather Forecasts.
NVIDIA Omniverse is a real-time virtual world simulation and 3D design collaboration platform that complements Modulus. It enables the real-time visualization and interactive exploration of digital twins using the output surrogate model from Modulus.
Ian Buck, Vice President of Accelerated Computing at NVIDIA, said, “Accelerated computing with AI at data center scale has the potential to deliver millionfold increases in performance to tackle challenges, such as mitigating climate change, discovering drugs and finding new sources of renewable energy. NVIDIA’s AI-enabled framework for scientific digital twins equips researchers to pursue solutions to these massive problems.”
Fourier neural operators and transformers enable the NVIDIA FourCastNet physics-ML model, trained on 10TB of Earth system data. As a step toward Earth-2 – FourCastNet emulates and predicts the behavior and risks of extreme weather events such as hurricanes and atmospheric rivers with greater confidence and up to 45,000x faster.
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