ReMaP: Macro Placement by Recursively Prototyping and Periphery-Guided Relocating

We introduce the ReMaP framework, which generates expert-quality macro placements through recursively prototyping and periphery-guided relocating. A key innovation is ABPlace, an angle-based analytical method that arranges macros along an ellipse to facilitate a rough distribution near the periphery, while optimizing dataflow, minimizing overlap, and ensuring convergence. Based on the results of ABPlace, an efficient heuristic is proposed to position macros along the chip’s periphery, mirroring practices often employed by experts. Our framework outperforms three leading macro placers in both WNS and TNS across eight test cases, achieving improvements up to 34.15% in WNS and 65.39% in TNS, as tested on the popular OpenROAD-flow-scripts infrastructure. Additionally, our parameter autotuning method further improves timing by 8.75%.