How to Advance Chip Design with Digital Twins and EDA

This episode explores the convergence of digital twin technology and Electronic Design Automation (EDA) in revolutionizing semiconductor design and testing. Against the backdrop of EDA's 50-60 year evolution, the discussion highlights how digital twins, virtual representations of physical systems, are being harnessed to improve product quality, accelerate time to market, and achieve sustainable manufacturing. The conversation begins with the evolution of EDA, from testing simple devices to managing complex integrated circuits using scan technology and fault models as early digital twins. More significantly, the integration of digital twins into EDA workflows enhances co-simulation across electrical, thermal, and mechanical domains, addressing challenges in accuracy and synchronization through partnerships and real silicon validation. As the discussion pivots to factory settings, the interaction between digital twins in EDA and smart factories enhances data transfer, using machine learning to improve simulation and design, while also ensuring data privacy by optimizing AI within individual company sites. Emerging industry patterns reflected in the discussion include the simplification of EDA for users, the expansion of data sharing across EDA tools via data lakes, and the collaboration between Siemens and Advantest to develop adaptive test methods, ultimately aiming for faster silicon bring-up and ramp times for customers.