arXiv:2507.14914cs.ROcs.AI2025-07被引 1

提出新芯片布局方法,显著减少信号穿通并提升元件摆放效率。

One Step Beyond: Feedthrough & Placement-Aware Rectilinear Floorplanner

  • 分三阶段优化:先粗调布局,再零间隙精修,最后动态调整模块边界。
  • 相比现有方法,平均降低6%的线长、5.16%的引脚穿通、29.15%的模块穿通。
  • 适合追求高精度布局与跨阶段协同优化的芯片设计工程师。

布局规划决定芯片上模块的形状与位置,对功耗、性能和面积(PPA)至关重要。但现有方法常无法与后续物理设计阶段集成,导致模块内元件摆放不佳且模块间穿通过多。为此,我们提出Flora,一种三阶段的穿通感知矩形布局规划器。第一阶段使用线网掩码和位置掩码技术,粗粒度优化HPWL和穿通;第二阶段在固定轮廓下通过局部调整模块形状实现零间隙布局,精细优化穿通并改善元件摆放;第三阶段采用快速树搜索法高效放置模块内的宏单元和标准单元,并根据结果调整模块边界,实现跨阶段优化。实验表明,Flora优于最新先进方法,平均降低6%的HPWL、5.16%的FTpin、29.15%的FTmod,组件摆放性能提升14%。

原文摘要 · Abstract (English)

Floorplanning determines the shapes and locations of modules on a chip canvas and plays a critical role in optimizing the chip's Power, Performance, and Area (PPA) metrics. However, existing floorplanning approaches often fail to integrate with subsequent physical design stages, leading to suboptimal in-module component placement and excessive inter-module feedthrough. To tackle this challenge, we propose Flora, a three-stage feedthrough and placement aware rectilinear floorplanner. In the first stage, Flora employs wiremask and position mask techniques to achieve coarse-grained optimization of HPWL and feedthrough. In the second stage, under the constraint of a fixed outline, Flora achieves a zero-whitespace layout by locally resizing module shapes, thereby performing fine-grained optimization of feedthrough and improving component placement. In the third stage, Flora utilizes a fast tree search-based method to efficiently place components-including macros and standard cells-within each module, subsequently adjusting module boundaries based on the placement results to enable cross-stage optimization. Experimental results show that Flora outperforms recent state-of-the-art floorplanning approaches, achieving an average reduction of 6% in HPWL, 5.16% in FTpin, 29.15% in FTmod, and a 14% improvement in component placement performance.

芯片布局穿通优化物理设计

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