I. Introduction
In modern industry, layout methods are typically divided into two stages: macro placement and standard cell placement. In the former, macros are placed in legal locations around the chip boundaries, while in the latter, standard cells are placed in the remaining space after all macros have been fixed[1]. As illustrated in Fig. 1, this process is repeated until the desired layout is achieved. However, the evaluation of layout results is typically conducted manually only after the wiring step, which can lead to multiple iterations in the physical design flow and a reduction in overall productivity. As machine learning AI algorithms continue to gain popularity and are increasingly applied in various fields, there has been a proliferation of machine learning-based algorithms that utilize machine learning to accelerate the physical design process.
Basic macro placement flow