IncreMacro: Incremental Macro Placement Refinement

作者：Yuan Pu, Tinghuan Chen, Zhuolun He, Jiajun Qin, Chen Bai, Haisheng Zheng, Yibo Lin, Bei Yu · 发表于：IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 年份：2025 · DOI：10.1109/tcad.2025.3531776 · 被引用次数：2 · 研究领域：Parallel Computing and Optimization Techniques

This article proposes$\textsf {IncreMacro}$, a novel approach for macro placement refinement in the context of integrated circuit (IC) design. The suggested approach iteratively and incrementally optimizes the placement of macros in order to enhance IC layout routability and timing performance. To achieve this,$\textsf {IncreMacro}$utilizes several methods, including kd-tree-based macro diagnosis, gradient-based macro shifting, constraint-graph-based LP for macro legalization, and diffusion-based cell migration. By employing these techniques iteratively,$\textsf {IncreMacro}$meets two critical solution requirements of macro placement: 1) pushing macros toward the chip boundary and 2) preserving the original macro relative positional relationship. The proposed approach has been incorporated into$\textsf {AutoDMP}$and$\textsf {DREAMPlace}~4.0$, and is evaluated on seven RISC-V benchmark circuits and four TILOS macro placement circuit designs at the 7-nm technology node. Experimental results show that, compared with the macro placement solution provided by$\textsf {AutoDMP}~(\textsf {DREAMPlace}~4.0$), our approach reduces routed wirelength by 15.1% (14.9%), improves the routed worst negative slack (WNS) and total negative slack (TNS) by 99.9 (82.6%) and 99.9% (81.3%), and reduces the total power consumption by 4.4% (4.3%). Meanwhile, compared with$\textsf {IncreMacro}$[1], our approach augmented with the cell migration algorithm improves the routed WNS and TNS by 24.7% and 23.1...