Human-Centered Agentic AI Comes To RTL Verification


For decades, productivity gains in electronic design automation (EDA) came from better engines. Faster solvers, higher-capacity simulators, and more scalable formal tools allowed design and verification teams to keep pace as designs grew larger. That model is no longer sufficient. Today’s design and verification bottleneck is not raw tool performance, but the coordination overhead required... » read more

Using Data And AI More Effectively In EDA


Key Takeaways The data being produced by EDA tools tends to be for human consumption and has weak semantics. Agents are attempting to create actionable information from unstructured data. The Model Context Protocol may provide AI with access to better data. Semiconductor design generates a lot of data, but how much of that is useful or currently being used by AI tools? And h... » read more

Microservice-Based LLM Agents Enable EDA Flow Automation (Duke Univ. and Univ. of Maryland)


A new technical paper titled "AutoEDA: Enabling EDA Flow Automation through Microservice-Based LLM Agents" was published by researchers at Duke University and University of Maryland. Abstract "Modern Electronic Design Automation (EDA) workflows, especially the RTL-to-GDSII flow, require heavily manual scripting and demonstrate a multitude of tool-specific interactions which limits scalabili... » read more