Cadence and Nvidia have expanded their long-standing partnership to accelerate the use of artificial intelligence, physics-based simulation, and digital twin technologies across engineering workflows, targeting industries ranging from semiconductor design to robotics and hyperscale AI infrastructure.
The collaboration brings together Cadence’s expertise in electronic design automation (EDA) and system design with Nvidia’s accelerated computing, CUDA-X libraries, and Omniverse platform, aiming to increase productivity and shorten development cycles across multiple engineering domains.
Anirudh Devgan, president and chief executive officer of Cadence, said the partnership reflects a broader shift taking place across the industry.
“Agentic AI and digital twins are reshaping the entire engineering landscape – from semiconductor design to planetary-scale AI systems,” Devgan said.
“Our expanded collaboration with Nvidia accelerates the convergence of design and physical realization, connecting the Cadence AgentStack, Physical AI Stack, and AI factory digital twins with Nvidia’s breakthroughs in accelerated computing to deliver unprecedented speed, accuracy and trust in simulation and system development.”
Jensen Huang, founder and CEO of Nvidia, added that advances in accelerated computing are fundamentally changing how engineering work is carried out.
“We are at an inflection point in computing – CUDA-accelerated computing and AI are reinventing the engineering process,” Huang said.
“For the first time, we can innovate in the digital world – exploring, testing, and optimizing ideas at unprecedented speed and scale – by building everything as full-fidelity digital twins first.
“Together, Nvidia and Cadence are bringing this vision to life – transforming how engineers design, build and operate the world.”
Faster design and simulation workflows
As part of the expanded partnership, Cadence is integrating Nvidia technologies into its EDA and system analysis tools, enabling significantly faster simulation and design processes.
The companies say engineering workflows could see speed improvements of up to 100 times through the use of AI-driven solvers and physics-based models.
Cadence customers and partners, including Ascendence, Argonne National Laboratory, Honda R&D, Samsung and SK Hynix, are already using Nvidia-accelerated solutions to shorten product development timelines.
Agentic AI in chip design
The collaboration also extends to agent-based AI systems designed to automate and optimize semiconductor development.
Cadence recently introduced its ChipStack AI Super Agent, which applies agentic AI to chip design and verification. The company says early deployments have demonstrated productivity gains of up to 10 times.
Building on this, Cadence has unveiled AgentStack, a system designed to coordinate multiple AI agents across the full semiconductor design process, from register-transfer level design to physical and system-level workflows.
Nvidia is acting as an early partner, using AgentStack within its own design processes and providing feedback to support broader industry deployment.
The approach represents a shift from traditional, manually driven workflows to automated systems capable of reasoning across complex design environments.
Bridging simulation and real-world deployment
Beyond chip design, the partnership is targeting physical AI systems, including robotics and autonomous machines.
By combining Cadence’s simulation tools with Nvidia’s Isaac robotics platforms and Cosmos models, the companies aim to close the “sim-to-real” gap – enabling systems to be trained, tested and validated in virtual environments before being deployed in real-world applications.
The workflow spans simulation, validation, and deployment, with continuous feedback loops supported by digital twin models. The companies say this approach could accelerate experimentation while improving safety and reliability.
Digital twins for AI factories
Another focus area is the development of digital twins for large-scale AI infrastructure.
Cadence is integrating Nvidia’s Omniverse-based tools to enable simulation and optimization of AI factories, including data centers built on Nvidia’s latest computing platforms.
These digital twins allow operators to test different configurations, power settings and cooling strategies before deploying physical systems.
According to the companies, simulations have shown that optimizing power usage could increase efficiency metrics such as “tokens per watt” by as much as 17 percent, with further gains possible through thermal optimization strategies.
Industry shift toward AI-driven engineering
The expanded partnership highlights a broader trend toward embedding AI across the entire engineering lifecycle – from initial design and simulation to deployment and operations.
Cadence showcased the combined technologies, including its AgentStack platform and digital twin solutions, at its CadenceLIVE 2026 event last week, where the companies also demonstrated how AI-driven workflows can help engineering teams move more quickly from concept to deployment.
While many of the capabilities remain in early stages of adoption, the collaboration underscores how AI and accelerated computing are increasingly being positioned as core infrastructure for next-generation engineering and industrial systems.
