{"title":"Yield Improvement for 3D Wafer-to-Wafer Stacked ICs Using Wafer Matching","authors":"M. Taouil, S. Hamdioui, E. Marinissen","doi":"10.1145/2699832","DOIUrl":null,"url":null,"abstract":"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).","PeriodicalId":7063,"journal":{"name":"ACM Trans. Design Autom. Electr. Syst.","volume":"1 1","pages":"19:1-19:23"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Trans. Design Autom. Electr. Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2699832","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
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).