Optimization of Macro Placement Using Genetic Algorithm

This thesis presents a novel approach to macro-layout in physical design, combining genetic algorithms with traditional design techniques. Genetic algorithms simulate the process of genetic evolution by natural selection, whereby the most environmentally adapted individuals are obtained through the evolution of reproduction from generation to generation. In this paper, the macro layout is represented by individuals, and the characteristics of the macro layout are used to constrain it. In the algorithm presented in this paper, each individual's adaptation action to their environmental context is used to represent the line length. The smaller the line length, the greater the macro layout's conformity to its constraints. Finally, the physical design of different macro layouts is compared with the timing obtained by STA tool. The final conversion time violation of macro layout applying the algorithm of this paper achieved an average reduction of 6.8% in violation and 17% in the number of violation paths compared to manual macro layout. The macro layout has been optimized.