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A New Length-Based Algebraic Multigrid Clustering Algorithm

机译:一种新的基于长度的代数多重网格聚类算法

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摘要

Clustering algorithms have been used to improve the speed and quality of placement. Traditionally, clustering focuses on the local connections between cells. In this paper, a new clustering algorithm that is based on the estimated lengths of circuit interconnects and the connectivity is proposed. In the proposed algorithm, first an a priori length estimation technique is used to estimate the lengths of nets. Then, the estimated lengths are used in a clustering framework to modify a clustering technique based on algebraic multigrid (AMG), that finds the cells with the highest connectivity. Finally, based on the results from the AMG-based process, clusters are made. In addition, a new physical unclustering technique is proposed. The results show a significant improvement, reductions of up to 40%, in wire length can be achieved when using the proposed technique with three academic placers on industry-based circuits. Moreover, the runtime is not significantly degraded and can even be improved.
机译:聚类算法已用于提高放置速度和质量。传统上,集群集中于单元之间的本地连接。在本文中,提出了一种基于估计的电路互连长度和连通性的新聚类算法。在提出的算法中,首先使用先验长度估计技术来估计网络的长度。然后,将估计的长度用于聚类框架中,以基于代数多重网格(AMG)修改聚类技术,从而找到具有最高连通性的单元。最后,基于基于AMG的过程的结果,进行了聚类。另外,提出了一种新的物理解簇技术。结果表明,当将所提出的技术与基于工业电路的三个学术布局器一起使用时,可以显着改善电线的长度,最多可减少40%。此外,运行时间不会显着降低,甚至可以改善。

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