Siemens Deploys AI to Speed Up Chip Design
Siemens has announced the integration of agentic AI into its Questa One platform to accelerate the design and verification of integrated circuits. The technology uses AI-driven workflows combined with configurable human expertise to achieve a faster and more reliable register-transfer level (RTL) sign-off. This approach is designed to preserve current investments while optimizing performance.
The move is part of a broader strategy by Siemens to embed generative and agentic AI across its entire Electronic Design Automation (EDA) portfolio. This new system, dubbed Fuse EDA AI, is designed to be purpose-built for the unique complexities of semiconductor and PCB design. It allows engineers to use natural language to interact with the design tools, automating tasks and speeding up the overall workflow. Agentic AI represents a significant step beyond simple automation or co-pilot assistants. These AI agents can autonomously make decisions, reason through complex design problems, and proactively explore different architectural possibilities to optimize for power, performance, and area (PPA). This is crucial in a field where design complexity is constantly increasing and the density of transistors on chips is beginning to saturate. The technology is being integrated with NVIDIA's NIM microservices and Nemotron models, which helps to accelerate system-on-a-chip (SoC) design and verification. For example, the Aprisa AI tool, part of the new suite, claims to deliver up to a 10x improvement in productivity and can reduce the time to "tapeout"—the final step in the design phase—by a factor of three. The Register-Transfer Level (RTL) stage is a critical phase in chip design where the functionality of a circuit is described in terms of data flow between hardware registers. Errors or inefficiencies at this stage can lead to costly delays. By accelerating RTL sign-off, Siemens aims to tackle a major bottleneck in the verification process, which often consumes the majority of a chip design cycle. This AI-driven approach is a direct response to a growing talent shortage in the semiconductor industry. By 2030, the U.S. alone is projected to face a shortfall of 67,000 semiconductor engineers. AI tools that can handle more of the complex, repetitive tasks allow human engineers to focus on higher-level problem-solving and innovation. Siemens EDA, formerly Mentor Graphics, is one of the "big three" in the EDA market, alongside Synopsys and Cadence, who are also investing heavily in AI. Siemens reported a 19% increase in sales last year, a growth rate higher than its main competitors. The company's strategy focuses on integrating AI to manage the increasing complexity of chip designs for applications like AI accelerators and automotive systems.
