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Cadence says AuraStack lifts PCB design productivity 15x
Cadence launched AuraStack, an agentic system for PCB and advanced packaging design that uses AI to orchestrate precise simulation tools.
Image: The Register
Cadence Design Systems has unveiled AuraStack, an agentic AI system aimed at helping electrical engineers design and test printed circuit boards (PCBs) and handle advanced packaging workflows. The pitch is not to replace precision engineering software with generative models, but to use AI as a layer that coordinates Cadence’s existing simulation and test tools.
According to Michael Jackson, CVP of Cadence’s system design and analysis division, AuraStack acts more like a natural-language control plane for complex engineering work than a standalone design engine.
“AI is amplifying the value of our engineering products and technologies.”
Cadence says AuraStack can integrate with a mix of open and proprietary models. Those models are used to plan and orchestrate multi-step design and verification workflows, while the underlying simulations continue to run at higher precision on CPUs, GPUs, and other accelerators.
Jackson described one example around IR reliability checks: identifying power management components, creating a simulation-ready power tree, running the simulation, and then feeding the results back to the designer. Cadence already automates many of these steps, he said, but a typical PCB or package design still involves thousands of tasks across development.
Jackson told The Register that 65 percent of an engineer’s day is spent navigating those tasks. By taking over that orchestration work, Cadence claims AuraStack can deliver a 15x boost to productivity, leaving engineers to focus on design choices instead of process overhead.
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Several large electronics companies, including Nvidia, have already signed up, according to the report.
The broader idea is familiar in HPC: use lower-precision AI systems to manage or accelerate workflows built on highly precise simulations. The Register notes that Nvidia has been a major advocate of that model. It also points to earlier work at the Department of Energy’s Sandia National Laboratories, where researchers used AI agents to develop and test hypotheses in what they described as a self-driving lab. Those systems did not use LLMs, relying instead on architectures such as variational auto-encoders.
Cadence has also built similar agents for digital and analog chip design, suggesting AuraStack is part of a wider effort to blend AI orchestration with traditional engineering compute.
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Marcus follows the money. He covers enterprise software, cloud architecture, and the tectonic shifts in Big Tech strategy. He translates dense earnings calls and complex M&A activity into actionable insights about where the industry is actually heading. If a tech giant makes a silent pivot, Marcus is usually the first to notice.
via The Register
