{"title":"利用李雅普诺夫指数和熵估计对过程变异性的敏感性","authors":"E. A. Ramos, Ricardo Reis","doi":"10.1109/ISVLSI59464.2023.10238486","DOIUrl":null,"url":null,"abstract":"The technology scaling of transistors makes them more susceptible to faults, such as those due to radiation effects and process variability. Faults related to process variability can cause circuits to operate outside their specification ranges. In most cases, simulations are used to analyze such effects, but simulations have high computational costs. This work aims to use the Mathematical Chaos Theory through the Lyapunov Exponents and the Entropy of a Circuit to analytically estimate the effects caused by the variability of the manufacturing process, resulting in a method that can estimate the variability to Power, Delay, and Power Delay Product (PDP) with an accuracy equivalent to simulation-based methods, but on average three hundred times faster.","PeriodicalId":199371,"journal":{"name":"2023 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","volume":"12 2.1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using Lyapunov Exponents and Entropy to Estimate Sensitivity to Process Variability\",\"authors\":\"E. A. Ramos, Ricardo Reis\",\"doi\":\"10.1109/ISVLSI59464.2023.10238486\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The technology scaling of transistors makes them more susceptible to faults, such as those due to radiation effects and process variability. Faults related to process variability can cause circuits to operate outside their specification ranges. In most cases, simulations are used to analyze such effects, but simulations have high computational costs. This work aims to use the Mathematical Chaos Theory through the Lyapunov Exponents and the Entropy of a Circuit to analytically estimate the effects caused by the variability of the manufacturing process, resulting in a method that can estimate the variability to Power, Delay, and Power Delay Product (PDP) with an accuracy equivalent to simulation-based methods, but on average three hundred times faster.\",\"PeriodicalId\":199371,\"journal\":{\"name\":\"2023 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)\",\"volume\":\"12 2.1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISVLSI59464.2023.10238486\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISVLSI59464.2023.10238486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Lyapunov Exponents and Entropy to Estimate Sensitivity to Process Variability
The technology scaling of transistors makes them more susceptible to faults, such as those due to radiation effects and process variability. Faults related to process variability can cause circuits to operate outside their specification ranges. In most cases, simulations are used to analyze such effects, but simulations have high computational costs. This work aims to use the Mathematical Chaos Theory through the Lyapunov Exponents and the Entropy of a Circuit to analytically estimate the effects caused by the variability of the manufacturing process, resulting in a method that can estimate the variability to Power, Delay, and Power Delay Product (PDP) with an accuracy equivalent to simulation-based methods, but on average three hundred times faster.