AI入侵EDA，要警惕

Core Viewpoint - The article discusses the importance of iterative processes in Electronic Design Automation (EDA) and highlights the challenges posed by decision-making in logic synthesis, emphasizing the need for integrated tools to manage multi-factor dependencies and improve timing convergence [1]. Group 1: EDA Process and Challenges - Iterative loops have been crucial in the EDA process for decades, especially as gate and line delays have become significant [1]. - The consequences of decisions in the EDA process can be far-reaching, affecting multiple other decisions, which complicates achieving acceptable timing [1]. - Serial tool operation can lead to major issues, and achieving timing convergence in logic synthesis is nearly impossible without a concept of iterative learning [1]. Group 2: Integration of Tools - The integration of decision tools, estimators, and checkers into a single tool addresses the issue of multi-factor dependencies, allowing for quick checks during decision-making [1]. - There is a growing need for such integrated functionalities across various fields, enabling users to guide tool operations based on their expertise [1]. Group 3: AI and Verification in EDA - AI hallucinations are recognized as a characteristic rather than a defect, with models generating plausible but not necessarily factual content [3]. - The use of retrieval-augmented generation (RAG) aims to control these hallucinations by fact-checking generated content, similar to practices in EDA [3]. - The industry has a strong emphasis on verification, which is crucial for ensuring the reliability of AI applications in EDA [5]. Group 4: Future Directions and Innovations - The industry is making progress in identifying necessary abstractions for validating ideas efficiently, with examples like digital twins and reduced-order models [6]. - A model generator capable of producing required abstract concepts for verification is deemed essential for mixed-signal systems [6]. - With proper verification, AI could lead to breakthroughs in performance and power efficiency, suggesting a need for a restructuring phase in the industry [6].