面向3D设计的两阶段并行分层感知划分

Yi-Hang Chen, Yi-Ting Chen, Juinn-Dar Huang
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引用次数: 2

摘要

与二维(2D)集成电路相比,3D集成电路是一项日益重要的突破性技术,具有提供显着性能和功能优势的潜力。这种新兴技术允许堆叠多层模具,并解决了通过硅通孔(tsv)的垂直连接问题。然而,尽管TSV被认为是一种很有前途的垂直连接解决方案,但它也占用了大量的硅资源,并引发了可靠性问题。由于这些挑战,最小化tsv的数量成为一个重要的设计问题。因此,在本文中,我们提出了一种具有发散阶段和收敛阶段的并行分层感知划分算法,用于最小化三维结构中的TSV。在发散阶段,我们采用OpenMP对2路最小切划分进行并行化,得到初始解,然后在收敛阶段对其进行细化。实验结果表明,与现有的几种方法相比,所提出的两阶段算法最多可减少39%的tsv数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two-staged parallel layer-aware partitioning for 3D designs
As compared to two-dimensional (2D) ICs, 3D integration is a breakthrough technology of growing importance that has the potential to offer significant performance and functional benefits. This emerging technology allows stacking multiple layers of dies and resolves the vertical connection issue by through-silicon vias (TSVs). However, though a TSV is considered a promising solution for vertical connection, it also occupies significant silicon estate and incurs reliability problem. Because of these challenges, minimizing the number of TSVs becomes an important design issue. Therefore, in this paper, we propose a parallel layer-aware partitioning algorithm, featuring both divergence stage and convergence stage, for TSV minimization in 3D structures. In the divergence stage, we employ OpenMP for the parallelization of 2-way min-cut partitioning and get the initial solution, and then refine it in the convergence stage. Experimental results show that the proposed two-staged algorithm can reduce the number of TSVs by up to 39% as compared to several existing methods.
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