Optimizing Semiconductor Circuit Layout Design Using Generative Adversarial Networks

As a core link in integrated circuit manufacturing, the efficiency and quality of semiconductor circuit layout design are directly related to the performance and cost of the product. Faced with the increasing complexity of circuits, traditional design methods can no longer meet the current demand for efficient and automated design. As a powerful generative model, generative adversarial networks (GANs) have made remarkable achievements in image processing, natural language processing and other fields, providing new ideas for the optimization of semiconductor circuit layout design. This paper deeply explores how to use GANs to optimize semiconductor circuit layout design, constructs a semiconductor circuit layout model, and conducts experimental training strategies for the model. Through experimental verification, this method significantly improves the design quality, reduces layout complexity, and thus improves circuit performance. The power consumption of the designed circuit is between 1.05w-7.8w.