Revolution or Hype? Seeking the Limits of Large Models in Hardware Design
It addresses the debate on whether large models are a revolution or hype for the electronic design automation community, providing an authoritative overview of this contentious trend.
This paper critically examines the practical capabilities and limitations of large AI models in hardware design, synthesizing expert perspectives on their potential to outperform or complement traditional EDA methods.
Recent breakthroughs in Large Language Models (LLMs) and Large Circuit Models (LCMs) have sparked excitement across the electronic design automation (EDA) community, promising a revolution in circuit design and optimization. Yet, this excitement is met with significant skepticism: Are these AI models a genuine revolution in circuit design, or a temporary wave of inflated expectations? This paper serves as a foundational text for the corresponding ICCAD 2025 panel, bringing together perspectives from leading experts in academia and industry. It critically examines the practical capabilities, fundamental limitations, and future prospects of large AI models in hardware design. The paper synthesizes the core arguments surrounding reliability, scalability, and interpretability, framing the debate on whether these models can meaningfully outperform or complement traditional EDA methods. The result is an authoritative overview offering fresh insights into one of today's most contentious and impactful technology trends.