Large Scale Circuit

Large-scale circuit research focuses on understanding and manipulating complex computational structures, whether in biological neural networks, digital circuits, or artificial neural networks. Current efforts concentrate on developing efficient algorithms and model architectures, such as transformers and graph neural networks, to analyze, design, and optimize these circuits, often employing techniques like tensor factorization and differentiable pruning. This work is significant for advancing both fundamental understanding of computation and for practical applications, including improved chip design, more efficient machine learning models, and enhanced interpretability of artificial intelligence.