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NVIDIA announced at NVIDIA GTC 2025 that leading computer-aided engineering (CAE) software vendors, including Ansys, Altair, Cadence, Siemens and Synopsys, are accelerating simulation tools by up to 50x with the NVIDIA Blackwell platform.
With accelerated software, along with NVIDIA CUDA-X libraries and blueprints to optimize performance, industries such as automotive, aerospace, energy, manufacturing and life sciences can reduce product development time and increase design accuracy while maintaining energy efficiency, NVIDIA reports.
“CUDA-accelerated physical simulation on NVIDIA Blackwell has enhanced real-time digital twins and is reimagining the entire engineering process,” says Jensen Huang, founder and CEO of NVIDIA. “The day is coming when virtually all products will be created and brought to life as a digital twin long before it is realized physically.”
Software providers can help customers develop digital twins with real-time interactivity and accelerate them with NVIDIA Blackwell technologies.
The ecosystem integrating Blackwell into its software includes Altair, Ansys, BeyondMath, Cadence, COMSOL, ENGYS, Flexcompute, Hexagon, Luminary Cloud, M-Star, NAVASTO, an Autodesk company, Neural Concept, nTop, Rescale, Siemens, Simscale, Synopsys and Volcano Platforms.
The NVIDIA Omniverse Blueprint for real-time digital twins is now generally available. The blueprint brings together NVIDIA CUDA-X libraries, NVIDIA PhysicsNeMo AI and the NVIDIA Omniverse platform—and is also adding the first NVIDIA NIM microservice for external aerodynamics, the study of how air moves around objects.
Learn more by watching the NVIDIA GTC keynote and register for sessions from NVIDIA.
Sources: Press materials received from the company and additional information gleaned from the company’s website.
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and…
Cut Retrieval-Augmented Generation (RAG) Hallucinations by 50%
Most teams hit the same wall with enterprise AI: LLMs that hallucinate, pipelines that don’t scale, and infrastructure that’s harder to design than the models themselves.
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