Tze-Hsin Wu, Po-Yuan Chen, Mincent Lee, Bin Lin, Cheng-Wen Wu, Chen-Hung Tien, Hung-Chih Lin, Hao Chen, C. Peng, Min-Jer Wang
{"title":"A memory yield improvement scheme combining built-in self-repair and error correction codes","authors":"Tze-Hsin Wu, Po-Yuan Chen, Mincent Lee, Bin Lin, Cheng-Wen Wu, Chen-Hung Tien, Hung-Chih Lin, Hao Chen, C. Peng, Min-Jer Wang","doi":"10.1109/TEST.2012.6401576","DOIUrl":null,"url":null,"abstract":"Error correction code (ECC) and built-in self-repair (BISR) schemes have been wildly used for improving the yield and reliability of memories. Many built-in redundancy-analysis (BIRA) algorithms and ECC schemes have been reported before. However, most of them focus on either BIRA algorithms or ECC schemes. In this paper, we propose an ECC-Enhanced Memory Repair (EEMR) scheme for yield improvement. Many modern memories are equipped with ECC in addition to BISR. We evaluate the back-end flow that combines both ECC and BIRA to determine whether yield can be improved by proper sequencing of the two steps. We also collect and identify important failure patterns and their distributions from over 100,000 sample memory instances, which are used to enhance the EEMR scheme that incorporates ECC. As ECC is failure pattern sensitive, careful evaluation from realistic failure bitmaps is necessary. We also verify the feasibility of implementing the proposed EEMR scheme by real test data. Experimental results from industrial 4Mb memory instances show that the proposed EEMR scheme gains over 2% instance yield on average, as compared with the traditional scheme. We also investigate the reliability of the EEMR scheme with different ECC specifications and BIRA algorithms.","PeriodicalId":353290,"journal":{"name":"2012 IEEE International Test Conference","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Test Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TEST.2012.6401576","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24
Abstract
Error correction code (ECC) and built-in self-repair (BISR) schemes have been wildly used for improving the yield and reliability of memories. Many built-in redundancy-analysis (BIRA) algorithms and ECC schemes have been reported before. However, most of them focus on either BIRA algorithms or ECC schemes. In this paper, we propose an ECC-Enhanced Memory Repair (EEMR) scheme for yield improvement. Many modern memories are equipped with ECC in addition to BISR. We evaluate the back-end flow that combines both ECC and BIRA to determine whether yield can be improved by proper sequencing of the two steps. We also collect and identify important failure patterns and their distributions from over 100,000 sample memory instances, which are used to enhance the EEMR scheme that incorporates ECC. As ECC is failure pattern sensitive, careful evaluation from realistic failure bitmaps is necessary. We also verify the feasibility of implementing the proposed EEMR scheme by real test data. Experimental results from industrial 4Mb memory instances show that the proposed EEMR scheme gains over 2% instance yield on average, as compared with the traditional scheme. We also investigate the reliability of the EEMR scheme with different ECC specifications and BIRA algorithms.