An illustration of a multi-chip package in a PCB. CADENCE DESIGN
Cadence announced three advancements in chip design automation this week at Nvidia’s GTC-Munich event, including a sovereign AI cloud for design, a new agentic AI “Super Agent” for PCB design, and a joint development project with Toyota Europe to evaluate high-fidelity external simulations using Nvidia Blackwell GPUs. Let’s take a look. (Note: Cadence Design and Nvidia are both clients of my firm, Cambrian-AI Research.)
A Sovereign Data Center For Chip Design
Cadence announced the availability of a sovereign AI data center in Munich to support its European customers. The data center will support Cadence OnCloud services, NVIDIA Vera CPU systems, Cadence Reality Digital Twin Platform, and the Cadence Millennium M2000 AI Supercomputer powered by the NVIDIA Blackwell platform. Cadence claims to be the first EDA vendor to deliver a sovereign AI platform for semiconductor, system and AI factory design in Europe, enabling European customers to design chips, advanced packaging, systems, physical AI applications and AI infrastructure while maintaining data residency within European jurisdiction.
The Cadence cloud integrates three layers of AI-driven engineering:
- Agentic AI: The Cadence AuraStack AI Super Agent, built with NVIDIA Nemotron open models, automates and coordinates electronic system design tasks, including schematic capture, placement, routing and multi-objective optimization.
- Computational software: Cadence EDA and SDA technologies use GPU-optimized NVIDIA CUDA-X libraries, including cuDSS, and NVIDIA Omniverse to accelerate power integrity, thermal analysis, electromagnetic characterization, and circuit simulation workflows.
- Accelerated computing: Cadence Millennium M2000 systems provide a shared, scalable foundation for the AuraStack AI Super Agent and Cadence engineering applications, powered by NVIDIA Blackwell GPUs.
Cadence Brings AI Super Agents to Nokia
Cadence has now built its agentic AI stack into what nay be the industry’s most comprehensive solution portfolio for agentic chip design automation, which can have a significant impact on engineering productivity and solution time-to-market. What started as the ChipStack AI Super Agent for SoC design and verification has now expanded to four solutions including InnoStack AI for digital implementation and signoff, AuraStack AI for PCB and advanced packaging design and ViraStack AI for custom and analog design.
Nokia is deploying the Cadence AuraStack AI Super Agent for PCB and Packaging design to advance electronic system design at scale. Using agentic AI in a secure, on-premises platform, Nokia is accelerating key design and analysis workflows by 5X while maintaining control of sensitive engineering data and intellectual property.
“AI gives engineering teams the speed to explore more designs and the insight to make better tradeoffs, while keeping proprietary data and expertise under their control,” said Tim Costa, vice president and general manager of industrial and computational engineering at Nvidia. “Nokia is bringing that capability inside its own environment, with Cadence agents built with Nvidia Nemotron open models and simulation. Together, they connect design automation with the power, thermal and electromagnetic analysis needed to evaluate each iteration, while keeping proprietary data and IP under Nokia’s control.”
The deployment establishes a new model for AI-driven engineering at leading systems companies. Nokia can use the AuraStack AI Super Agent to automate engineering tasks, explore complex system tradeoffs and close multiphysics analysis loops across heterogeneous electronic systems. The modular Millennium architecture enables Nokia to expand capacity as requirements grow and run multiple agentic engineering workloads in parallel.
Cadence and Toyota Team Up for Automotive Simulation
Cadence is more than an EDA firm these days, having expanded into system, biological, and mechanical design and analysis. Cadence announced it is collaborating with Toyota Motor Europe (TME) to evaluate high-fidelity external aerodynamics and aeroacoustic simulation on TME’s Aygo X model using the Cadence Fidelity CFD (Computational Fluid Dynamics) software. The work demonstrates how accelerated computing can reduce turnaround time for CFD workflows while supporting the generation of richer simulation datasets for building the foundation for physics-based AI models.
“Our collaboration with Cadence demonstrates how scalable high-fidelity CFD on NVIDIA GPUs can achieve turnaround time significantly lower than our CPU-based workflow, without sacrificing accuracy,” said Antoine Delacroix, senior manager, Vehicle Performance Engineering R&D at Toyota Motor Europe. Such fast aerodynamics simulation-based workflow supports our journey to make ever better cars.”
Interestingly, this work has demonstrated the scalable performance provided by modern GPUs. Often, CFD work is run on CPUs or workstation-class GPUs used for the design work, such as the Nvidia RTX Pro 6000. This work revealed the nearly linear speedup that can be achieved by adding data center class GPUs.
Simulation results on the RTX Pro (left) vs DGX B200 (right). CADENCE DESIGN
For the same Aygo X simulation, the right-hand graph shows that the eight-GPU B200 configuration reaches convergence about 5X faster than the RTX PRO 6000 Blackwell Server Edition. It also shows the difference in per-GPU performance: the RTX PRO 6000 requires 32 GPUs to approach the convergence time achieved by the B200 with only eight GPUs.
GPUs in the Design World
Historically, most design software ran on CPUs, partly due to the per-core pricing models in use and partly due to the engineering effort needed to port and paralleliz these applications to GPUs. Now
Disclosures: This article expresses the author’s opinions and should not be taken as advice to purchase from or invest in the companies mentioned. Cambrian-AI Research is fortunate to have had many, if not most, semiconductor firms as our clients, including Blaize, BrainChip, Cadence Design, Cerebras, D-Matrix, Eliyan, Esperanto, Flex, GML, Groq, IBM, Intel, Micron, NVIDIA, Qualcomm Technologies, Si-Five, SiMa.ai, Synopsys, Ventana Microsystems, Tenstorrent and scores of investment clients. We have no investment positions in any of the companies mentioned in this article, with the exception of Nvidia.