Session

DescriptionModern analog IC design faces challenges like increasing complexity, optimization, PVT variations, and simulation bottlenecks. Traditional methods struggle with large design spaces and reliability. LLMs and deep learning technologies address these issues by automating tasks, managing PVT variations, and reducing simulation costs. This session will cover the topics reinforcement learning for variation-aware designs, transfer learning for system-level optimization, universal neural simulators, GPU-accelerated passivity enforcement, and image-graph fusion for IR drop prediction, demonstrating AI’s role in optimizing and enhancing analog IC design.