2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED)最新文献

Comparison of Manifold Learning Algorithms for Rapid Circuit Defect Extraction in SPICE-Augmented Machine Learning spice增强机器学习中快速电路缺陷提取的流形学习算法比较

2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED) Pub Date : 2022-04-01 DOI: 10.1109/wmed55302.2022.9758032

Vasu Eranki, T. Lu, H. Wong

{"title":"Comparison of Manifold Learning Algorithms for Rapid Circuit Defect Extraction in SPICE-Augmented Machine Learning","authors":"Vasu Eranki, T. Lu, H. Wong","doi":"10.1109/wmed55302.2022.9758032","DOIUrl":"https://doi.org/10.1109/wmed55302.2022.9758032","url":null,"abstract":"Identifying the source of integrated circuit (IC) degradation and being able to track its degradation via its electrical characteristics (e.g. the Voltage Transfer Characteristics, VTC, of an inverter) is very useful in failure analysis. This is because the electrical measurement is non-destructive, low-cost, and rapid. However, the extraction of defects from electrical characteristics requires significant domain expertise. To reduce or even obviate the need for domain expertise so that the process can be automatic for various circuits, one may use manifold learning. As a type of machine learning (ML), manifold learning also requires a large amount of accurate training data. To obtain enough defect training data, which is almost impossible from experiments, one may use SPICE simulation. Based on our previous work of using AutoEncoder (AE) to perform SPICE-augmented ML to extract the pMOS and nMOS source contact resistances from the inverter VTC, in this paper, we compare the efficacy of using another 6 types of manifold learning. They are used to predict the experimental result and it is found that most of them have reasonable performance although the AE is still the best (R2=0.9). However, when including also the variation of PMOS width (as a weak perturbation to the data), algorithms such as Locally Linear Embedding (LLE) are found to perform better than AE (R2=0.72) with LLE (R2=0.83) being the best. Therefore, multiple manifold learnings are suggested to be used in parallel in real production to enhance accuracy.","PeriodicalId":444912,"journal":{"name":"2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122800729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

New distributed controlling architecture for high performances NAND generation 高性能NAND生成的新型分布式控制体系结构

2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED) Pub Date : 2022-04-01 DOI: 10.1109/wmed55302.2022.9758017

Luca Nubile, Walter Di Francesco, Riccardo Cardinali, Luca De Santis, M. Gallese, Gianfranco Valeri, Jeff Tsai, Dheeraj Srinivasan, A. Mohammadzadeh, T. Vali

{"title":"New distributed controlling architecture for high performances NAND generation","authors":"Luca Nubile, Walter Di Francesco, Riccardo Cardinali, Luca De Santis, M. Gallese, Gianfranco Valeri, Jeff Tsai, Dheeraj Srinivasan, A. Mohammadzadeh, T. Vali","doi":"10.1109/wmed55302.2022.9758017","DOIUrl":"https://doi.org/10.1109/wmed55302.2022.9758017","url":null,"abstract":"This paper describes the controlling architecture changes introduced in the last generation of NAND flash. The pressing demand for performance from NAND systems required an increase in the working frequencies and task parallelism of the logical executors. In the new controller generation, the algorithm execution has been distributed creating a controlling hierarchy formed by a central executor which performs the main flow and the complex calculations at low frequency, to save power, supported by small but fast machines, placed near the slower peripherals. These machines, called HW (HardWare) accelerators, drive slower peripherals at high speed and in parallel with main flow to increase performances, but are launched only on request to avoid important power impacts. The new architecture proposed in this work, allowed to deliver an outstanding tprog effective on new generation devices, opening a path to even more aggressive tprog in the future with newly identified optimizations. These techniques are in practice on products currently in production.","PeriodicalId":444912,"journal":{"name":"2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116777692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE WMED 2022 High School Program IEEE WMED 2022高中课程

2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED) Pub Date : 2022-04-01 DOI: 10.1109/wmed55302.2022.9758027

引用次数: 0

IEEE WMED 2022 Keynote Address [8 abstracts] IEEE WMED 2022主题演讲[8个摘要]

2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED) Pub Date : 2022-04-01 DOI: 10.1109/wmed55302.2022.9758006

引用次数: 0

IEEE WMED 2022 Technical Program IEEE WMED 2022技术计划

2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED) Pub Date : 2022-04-01 DOI: 10.1109/wmed55302.2022.9758015

引用次数: 0

IEEE WMED 2022 Organizing Committee IEEE WMED 2022组委会

2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED) Pub Date : 2022-04-01 DOI: 10.1109/wmed55302.2022.9758031

引用次数: 0

First order correction of EELS measurements based on experimental ADF imaging 基于实验ADF成像的EELS测量一阶校正

2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED) Pub Date : 2022-04-01 DOI: 10.1109/wmed55302.2022.9758034

Y. Liao, R. Goodwin, W. Harlow, Curt Sorensen, Tom Kari, Aaron J. Miller, Robert Wilkin, S. Williams

{"title":"First order correction of EELS measurements based on experimental ADF imaging","authors":"Y. Liao, R. Goodwin, W. Harlow, Curt Sorensen, Tom Kari, Aaron J. Miller, Robert Wilkin, S. Williams","doi":"10.1109/wmed55302.2022.9758034","DOIUrl":"https://doi.org/10.1109/wmed55302.2022.9758034","url":null,"abstract":"In Physical Failure TEM (Transmission Electron Microscopy) analysis with EELS (Electron Energy Loss Spectroscopy) technique, it is common to directly evaluate the composition of certain elements side-by-side and sample-to-sample, based on the extracted intensity of the corresponding core-loss signals after background removal. However, there can be non-uniformity of TEM sample thickness, difference of sandwiched structures, and/or mixing of different elements between the compared regions. Such variations of local thickness and/or structures can cause incorrect signal extraction in EELS measurement due to the nature of interaction of incident electrons with matter. This short communication provides the first order correction based on ADF (Annular Dark Field) intensity, collected by (High Angle Annular Dark Field), in combination with theoretical simulation of electron interaction of incident electrons with materials, and the direct measurements of the wedged-TEM samples and transmitted beam current of incident electrons, although it does not aim to address all artificial effects from EELS quantification. The electron elastic and inelastic scatterings depends on both the sample thickness and effective atomic number. Their correlation in corporation with multiple scattering are computed with LenzPlus simulation proposed by R. F. Egerton. This paper theoretically and experimentally discusses the cause of EELS inaccuracy and then proposes a first order correction technique which derives a more accurate elemental quantification in EELS measurements. This is especially useful in semiconductor PFA (Physical Failure Analysis) when elemental quantification is need site-by-site and sample-by-sample when thickness variation and/or structural variation exist. Finally, an example of quantification improvement with a structure of Si active area in DRAM (Dynamic Random-Access Memory) is presented.","PeriodicalId":444912,"journal":{"name":"2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125578891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE WMED 2022 Sponsors IEEE WMED 2022赞助商

2022 IEEE 19th Annual Workshop on Microelectronics and Electron Devices (WMED) Pub Date : 2022-04-01 DOI: 10.1109/wmed55302.2022.9758030

引用次数: 0