利用晶圆匹配提高3D晶圆堆叠ic的良率

M. Taouil, S. Hamdioui, E. Marinissen
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引用次数: 7

摘要

采用通硅过孔(tsv)的三维堆叠集成电路(3D-SIC)是一种新兴技术,与传统集成电路相比,它提供了异构集成、更高的性能和更低的功耗。使用晶圆对晶圆(W2W)堆叠3d - sic具有几个优点,例如高堆叠吞吐量,高TSV密度,以及处理薄晶圆和小模具的能力。然而,由于不能防止好模具在坏模具上堆积,因此它的复合产量很低,反之亦然。本文探讨了晶圆匹配作为提高良率的一种手段。它首先定义了一个完整的晶圆匹配框架,由不同的场景组成,每个场景都有一个匹配过程(定义晶圆选择的顺序)、一个匹配标准(定义是否匹配好或坏的晶圆)、晶圆旋转(定义晶圆是否旋转)和一个存储库类型的组合。储存库类型指定储存库是在每个晶圆选择之后立即填充(即,运行储存库)还是在所有晶圆匹配之后填充(即,静态储存库)。对该框架先前工作的映射显示,现有的研究主要是探索基于静态存储库的场景。因此,本文将分析基于运行的存储库的场景。仿真结果表明,基于运行库的场景相对于随机W2W堆叠,复合收率提高了13.4%;这种改进很大程度上取决于堆积模具的数量、模具成品率、储存库大小以及所使用的匹配过程。此外,结果表明,基于运行存储库的场景在显著减少运行时(三个数量级)和降低内存复杂性(就堆栈大小而言,从指数到线性)方面的产量提高优于静态存储库。
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Yield Improvement for 3D Wafer-to-Wafer Stacked ICs Using Wafer Matching
Three-Dimensional Stacked IC (3D-SIC) using Through-Silicion Vias (TSVs) is an emerging technology that provides heterogeneous integration, higher performance, and lower power consumption compared to traditional ICs. Stacking 3D-SICs using Wafer-to-Wafer (W2W) has several advantages such as high stacking throughput, high TSV density, and the ability to handle thin wafers and small dies. However, it suffers from low-compound yield as the stacking of good dies on bad dies and vice versa cannot be prevented. This article investigates wafer matching as a means for yield improvement. It first defines a complete wafer matching framework consisting of different scenarios, each a combination of a matching process (defines the order of wafer selection), a matching criterion (defines whether good or bad dies are matched), wafer rotation (defines either wafers are rotated or not), and a repository type. The repository type specifies whether either the repository is filled immediately after each wafer selection (i.e., running repository) or after all wafers are matched (i.e., static repository). A mapping of prior work on the framework shows that existing research has mainly explored scenarios based on static repositories. Therefore, the article analyzes scenarios based on running repositories. Simulation results show that scenarios based on running repositories improve the compound yield with up to 13.4% relative to random W2W stacking; the improvement strongly depends on the number of stacked dies, die yield, repository size, as well as on the used matching process. Moreover, the results reveal that scenarios based on running repositories outperform those of static repositories in terms of yield improvement at significant runtime reduction (three orders of magnitude) and lower memory complexity (from exponential to linear in terms of stack size).
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