Siemens Unveils AI-Powered Library Characterization to Accelerate Semiconductor Design

Why It Matters

By slashing library characterization time, Siemens empowers chip designers to meet tighter product schedules and reduce development costs, a critical advantage as process nodes become more complex. The AI‑centric approach also raises the performance baseline for the entire EDA ecosystem.

Key Takeaways

• Solido Characterizer cuts Liberty file generation from weeks to days
• AI engine delivers 5× speedup; LibSPICE adds 2× more performance
• Supports emerging LVF format and multi‑PVT creation across nodes
• Enables real‑time QA via Solido Analytics, streamlining redesign cycles

Pulse Analysis

The semiconductor industry faces mounting pressure to deliver ever‑more intricate designs on shrinking timelines. Traditional library characterization, which translates transistor behavior into SPICE‑based Liberty models, is a bottleneck that can consume weeks of compute resources. As process nodes advance, the number of process‑voltage‑temperature (PVT) corners and emerging data formats like LVF multiply, demanding faster, more accurate solutions. AI‑enhanced EDA tools are emerging as a remedy, using machine learning to predict circuit behavior and automate repetitive tasks, thereby freeing engineers to focus on innovation.

Siemens' Solido™ Characterizer builds on this trend by combining a high‑performance AI engine with its proprietary LibSPICE simulator. The AI component alone delivers a five‑fold speed increase for multi‑PVT and LVF workflows, while LibSPICE adds another two‑fold boost, culminating in an overall seven‑times acceleration. Integrated with Solido Analytics, the platform offers live quality‑assurance dashboards, automated reruns, and seamless handoff to Solido Generator, which can synthesize additional library views without further SPICE simulation. This end‑to‑end automation not only trims development cycles but also preserves the fidelity of the generated models, a crucial factor for high‑volume manufacturing.

Early deployments underscore the commercial relevance of the solution. GlobalFoundries leveraged Solido Characterizer to achieve a 20‑30% speedup while maintaining production‑grade accuracy, and Anatrix cited the tool’s ability to validate radiation‑hardened libraries with confidence. By delivering rapid, reliable library generation, Siemens positions itself as a catalyst for faster time‑to‑market across the semiconductor supply chain, pressuring competing EDA vendors to adopt comparable AI capabilities. As chip designs grow in complexity, AI‑driven characterization is likely to become a standard expectation rather than a differentiator.