Circuit Topology

Circuit topology research focuses on automating the design of electronic circuits, aiming to optimize performance metrics like power consumption and bandwidth while reducing design time. Current efforts leverage machine learning, employing graph neural networks (GNNs) and large language models (LLMs) to generate and refine circuit designs, often incorporating evolutionary algorithms or supervised learning techniques. This research significantly impacts electronic design automation, potentially accelerating the development of complex circuits for applications ranging from artificial intelligence accelerators to radio-frequency systems. The development of comprehensive datasets and benchmarks is also a key focus, enabling more robust evaluation and comparison of different approaches.