The invention relates to the technical field of circuit wiring, in particular to an AI-based circuit wiring
system, method, medium and equipment, and the
system comprises an input module, a preprocessing module, a
deep learning module, a topology loss calculation module, a candidate
layout generation module, a
graphical user interface module, a man-
machine interaction module and an output module. The input module is used for receiving each device of an analog circuit and physical size information thereof, and describing a description file of a topology constraint relationship between device pairs; the preprocessing module performs normalization
processing on the size information of the device; the
deep learning module is a graph structure neural network, and an output layer of the graph structure neural network outputs two-dimensional plane position coordinates corresponding to the devices; the topology loss calculation module defines a topology
loss function and calculates an error value in a graph structure neural network training process, and the candidate
layout generation module automatically generates a plurality of device candidate
layout schemes meeting the topology
loss function based on the trained graph structure neural network; the
graphical user interface module is used for displaying candidate layout schemes and the error component value of each scheme; the man-
machine interaction module provides a layout
fine tuning function through a
graphical user interface; the output module is used for outputting a final device layout scheme after manual
fine tuning or automatic generation; according to the invention, the design efficiency and quality of the layout of the analog
integrated circuit are improved, and the requirements of modern
integrated circuit design for rapid iteration and efficient layout are met.