The New Engineering Stack at NVIDIA GTC 2026

24 Feb 2026 • 4 minute read

Together, accelerated computing and agentic AI are redefining both the engine and the interface of modern engineering. This transformation is driven by the deep, ongoing collaboration between Cadence and NVIDIA, combining AI infrastructure and agentic AI to redefine the foundation of modern engineering across electronics, systems, and life sciences. By co-optimizing Cadence's design, simulation, and analysis software with NVIDIA's accelerated computing roadmap—from the NVIDIA Grace Blackwell system and Blackwell platform systems, through the latest GB300 NVL72 innovations, and toward the upcoming Vera Rubin platform—the collaboration enables engineers to tackle problems that were previously impractical or impossible with traditional CPU-based approaches.

Spanning electronic design automation, system design and analysis, digital twins, and molecular sciences, this work accelerates core simulation and analysis technologies while embedding full-stack agentic AI directly into design workflows to dramatically increase throughput, improve accuracy, automate insight generation, and enhance engineering productivity. The result is a new class of design platform that enables teams to explore larger design spaces, run longer and more realistic simulations, and make better, faster decisions—shortening time to market while increasing confidence in design outcomes.

NVIDIA GTC 2026 is where the world comes together to align on these technologies and ideas, and where you can see firsthand how this collaboration is shaping the future of design—join us at GTC 2026 to learn about it all; it's a must-attend moment. Register Now for GTC.

Must-Attend Cadence Sessions

GTC 2026 is packed with opportunities to learn from industry leaders, and Cadence has several can't-miss sessions, including:

AI-Accelerated Design: From Hyperscale Data Centers to Molecular Discovery

(Session EX82195) The pace of AI-driven design innovation has accelerated dramatically since early 2025. With the introduction of Cadence's AI-optimized Millennium M2000 Supercomputer built on NVIDIA, engineers and scientists now have the unprecedented capability to tackle the hardest problems in semiconductor design, system integration, and life sciences. In this session, discover how Cadence and NVIDIA are shaping a unified AI design ecosystem—integrating agentic AI workflows, physics-based models, and simulation-driven approaches to accelerate breakthroughs in chip design, advanced packaging, physical AI, and molecular discovery. Learn how next-generation infrastructure and tools are driving continuous innovation across every scale—from silicon and systems to data centers and molecules. Key takeaways include:

AI-Accelerated Design Across Domains
Unified AI Design Ecosystem
Next-Generation Infrastructure Driving Scale

How to Build Planetary-Scale AI Infrastructure

Chris Dolan, Chief Data Center Officer, Crusoe Energy Systems
Scott Wallace, Director Data Center Engineering, NVIDIA
Vivek Mishra, Corporate VP, Cadence
Natasha Nelson, CTO of Services and VP of EcoStruxure Power, Schneider Electric
Catherine Kniker, Chief Marketing and Sustainability Officer, PTC

(Session S81671) Gigawatt-scale AI facilities are pushing data center infrastructure beyond the limits of traditional design and operations workflows. Siloed approaches to buildings, power, cooling, and compute make it difficult to scale efficiently while meeting energy and sustainability requirements. This panel explores how simulation-based co-design and physically accurate digital twins are being used to plan and operate large-scale AI infrastructure. Industry leaders will discuss how these methods help evaluate tradeoffs earlier, improve efficiency, and better align facility, power, thermal, and compute decisions. Key takeaways include:

Learn the radical new approach required for gigawatt-scale AI factories, co-designing the building, power, cooling, and compute stacks simultaneously to achieve extreme energy efficiency and scale.
Unifying Design with Digital Twins: Understand how industry leaders are leveraging AI-powered digital twins, OpenUSD, and physically accurate simulation environments to accelerate infrastructure design and optimize real-time operations.
Maximize Tokens per Watt: Learn how integrating power, cooling, and compute design is the only pathway to sustainable, gigawatt-scale AI deployment.

Engage with Cadence in Booth 834

Our presence at GTC 2026 goes beyond sessions. Make time to stop by the Cadence booth for demos and discussion! Find us next to the NVIDIA booth.

Demo #1: AI for Design: Chips, Systems, and Molecular Design Accelerated

Cadence is showcasing its AI-driven accelerated design solution spanning semiconductors, advanced packaging and 3D-IC, system design and analysis, and molecular science, developed through broad collaboration with NVIDIA for designing the next generation of AI and intelligent systems. The demo highlights the tight integration of Cadence applications with NVIDIA CUDA -X libraries, NVIDIA Omniverse, and NVIDIA Nemotron, powered by the Cadence Millennium M2000 AI Supercomputer built on the NVIDIA Blackwell platform. This combination dramatically reduces simulation and optimization turnaround times while enabling unprecedented design scale. Technologies for acceleration include analog/mixed-signal simulation, digital implementation, electromagnetic analysis, thermal and voltage analysis, signal and power integrity, package and PCB design, CFD, and biosimulation.

Demo #2: Design for AI: Scaling AI Factory Digital Twin Design

Cadence is presenting an NVIDIA Omniverse DSX Blueprint-based digital twin to accelerate gigawatt-scale AI factory buildouts and unlock billions of dollars in potential revenue gains by simulating real AI workload scenarios. The Reality Digital Twin Platform, integrated with NVIDIA Omniverse libraries, elevates data center design and operations from a measure-and-react approach to a predict-and-optimize model. At the AI factory scale, this transformation is enabled by high-fidelity, physics-accurate behavioral models combined with AI surrogate models and advanced efficiency capabilities that capture how AI factories respond to lifecycle changes in workloads, configurations, and environmental conditions. This foundation enables continuous, real-time performance assessment and optimization—maximizing compute output per dollar and per watt, reducing the risk, and accelerating the transition to sustainable, scalable AI operations—further enhanced by high-fidelity cooling and thermal simulation and seamless interoperability through the Omniverse-powered Reality DT Experience.

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