{"title":"扫描链移位过程中峰值红外降的gpu加速估计和目标降低","authors":"Shiling SHI, Stefan HOLST, Xiaoqing WEN","doi":"10.1587/transinf.2023edp7011","DOIUrl":null,"url":null,"abstract":"High power dissipation during scan test often causes undue yield loss, especially for low-power circuits. One major reason is that the resulting IR-drop in shift mode may corrupt test data. A common approach to solving this problem is partial-shift, in which multiple scan chains are formed and only one group of scan chains is shifted at a time. However, existing partial-shift based methods suffer from two major problems: (1) their IR-drop estimation is not accurate enough or computationally too expensive to be done for each shift cycle; (2) partial-shift is hence applied to all shift cycles, resulting in long test time. This paper addresses these two problems with a novel IR-drop-aware scan shift method, featuring: (1) Cycle-based IR-Drop Estimation (CIDE) supported by a GPU-accelerated dynamic power simulator to quickly find potential shift cycles with excessive peak IR-drop; (2) a scan shift scheduling method that generates a scan chain grouping targeted for each considered shift cycle to reduce the impact on test time. Experiments on ITC'99 benchmark circuits show that: (1) the CIDE is computationally feasible; (2) the proposed scan shift schedule can achieve a global peak IR-drop reduction of up to 47%. Its scheduling efficiency is 58.4% higher than that of an existing typical method on average, which means our method has less test time.","PeriodicalId":55002,"journal":{"name":"IEICE Transactions on Information and Systems","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GPU-Accelerated Estimation and Targeted Reduction of Peak IR-Drop during Scan Chain Shifting\",\"authors\":\"Shiling SHI, Stefan HOLST, Xiaoqing WEN\",\"doi\":\"10.1587/transinf.2023edp7011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High power dissipation during scan test often causes undue yield loss, especially for low-power circuits. One major reason is that the resulting IR-drop in shift mode may corrupt test data. A common approach to solving this problem is partial-shift, in which multiple scan chains are formed and only one group of scan chains is shifted at a time. However, existing partial-shift based methods suffer from two major problems: (1) their IR-drop estimation is not accurate enough or computationally too expensive to be done for each shift cycle; (2) partial-shift is hence applied to all shift cycles, resulting in long test time. This paper addresses these two problems with a novel IR-drop-aware scan shift method, featuring: (1) Cycle-based IR-Drop Estimation (CIDE) supported by a GPU-accelerated dynamic power simulator to quickly find potential shift cycles with excessive peak IR-drop; (2) a scan shift scheduling method that generates a scan chain grouping targeted for each considered shift cycle to reduce the impact on test time. Experiments on ITC'99 benchmark circuits show that: (1) the CIDE is computationally feasible; (2) the proposed scan shift schedule can achieve a global peak IR-drop reduction of up to 47%. Its scheduling efficiency is 58.4% higher than that of an existing typical method on average, which means our method has less test time.\",\"PeriodicalId\":55002,\"journal\":{\"name\":\"IEICE Transactions on Information and Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEICE Transactions on Information and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1587/transinf.2023edp7011\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEICE Transactions on Information and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1587/transinf.2023edp7011","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
GPU-Accelerated Estimation and Targeted Reduction of Peak IR-Drop during Scan Chain Shifting
High power dissipation during scan test often causes undue yield loss, especially for low-power circuits. One major reason is that the resulting IR-drop in shift mode may corrupt test data. A common approach to solving this problem is partial-shift, in which multiple scan chains are formed and only one group of scan chains is shifted at a time. However, existing partial-shift based methods suffer from two major problems: (1) their IR-drop estimation is not accurate enough or computationally too expensive to be done for each shift cycle; (2) partial-shift is hence applied to all shift cycles, resulting in long test time. This paper addresses these two problems with a novel IR-drop-aware scan shift method, featuring: (1) Cycle-based IR-Drop Estimation (CIDE) supported by a GPU-accelerated dynamic power simulator to quickly find potential shift cycles with excessive peak IR-drop; (2) a scan shift scheduling method that generates a scan chain grouping targeted for each considered shift cycle to reduce the impact on test time. Experiments on ITC'99 benchmark circuits show that: (1) the CIDE is computationally feasible; (2) the proposed scan shift schedule can achieve a global peak IR-drop reduction of up to 47%. Its scheduling efficiency is 58.4% higher than that of an existing typical method on average, which means our method has less test time.
期刊介绍:
Published by The Institute of Electronics, Information and Communication Engineers
Subject Area:
Mathematics
Physics
Biology, Life Sciences and Basic Medicine
General Medicine, Social Medicine, and Nursing Sciences
Clinical Medicine
Engineering in General
Nanosciences and Materials Sciences
Mechanical Engineering
Electrical and Electronic Engineering
Information Sciences
Economics, Business & Management
Psychology, Education.