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A Secure and Cost-Effective Training Framework Atop Serverless Computing for Object Detection in Blasting

computer Modeling in Engineering & Sciences 2024年第5期139卷 2139-2154页

作者： Tianming Zhang Zebin Chen Haonan Guo Bojun Ren Quanmin Xie Mengke Tian Yong Wang Department of Computer and Science Shanghai Jiaotong UniversityShanghai200240China Aerospace System Engineering Shanghai Shanghai200240China State Key Laboratory of Precision Blasting Jianghan UniversityWuhan430056China Beijing Microelectronics Technology Institute Beijing100076China

The data analysis of blasting sites has always been the research goal of relevant *** rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection in the field of *** Computing can provide a variety of computing services for people without hardware foundations and rich software development experience,which has aroused people’s interest in how to use it in the field ofmachine *** this paper,we design a distributedmachine learning training application based on the AWS Lambda *** on data parallelism,the data aggregation and training synchronization in Function as a Service(FaaS)are effectively *** also encrypts the data set,effectively reducing the risk of data *** rent a cloud server and a Lambda,and then we conduct experiments to evaluate our *** results indicate the effectiveness,rapidity,and economy of distributed training on FaaS.

关键词： Serverless computing object detection blasting

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Large circuit models: opportunities and challenges

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Science China(Information Sciences) 2024年第10期67卷 25-66页

作者： Lei CHEN Yiqi CHEN Zhufei CHU Wenji FANG Tsung-Yi HO Ru HUANG Yu HUANG Sadaf KHAN Min LI Xingquan LI Yu LI Yun LIANG Jinwei LIU Yi LIU Yibo LIN Guojie LUO Hongyang PAN Zhengyuan SHI Guangyu SUN Dimitrios TSARAS Runsheng WANG Ziyi WANG Xinming WEI Zhiyao XIE Qiang XU Chenhao XUE Junchi YAN Jun YANG Bei YU Mingxuan YUAN Evangeline F.Y.YOUNG Xuan ZENG Haoyi ZHANG Zuodong ZHANG Yuxiang ZHAO Hui-Ling ZHEN Ziyang ZHENG Binwu ZHU Keren ZHU Sunan ZOU Huawei Noah’s Ark Lab School of Integrated Circuits Peking University Faculty of Electrical Engineering and Computer Science Ningbo University Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Department of Computer Science and Engineering The Chinese University of Hong Kong School of Integrated Circuits Southeast University Huawei HiSilicon Peng Cheng Laboratory School of Computer Science Peking University School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University School of Artificial Intelligence Shanghai Jiao Tong University

Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.

关键词： AI-rooted EDA large circuit models (LCMs) multimodal circuit representation learning circuit optimization

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Numerical Elucidation of the Electrothermal Characteristics of Gate-All-Around FET Devices 11

Numerical Elucidation of the Electrothermal Characteristics ...

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11th IEEE International Conference on systems and Control, ICSC 2023

作者： Nasri, Faouzi Salama, Husien Laboratory of Thermal Processes CRTEn Borj-Cedria Tunisia Tunisia Research Center for Microelectronics and Nanotechnology Sousse Tunisia Computer System Institute Boston United States

ISBN: (纸本)9798350304886

The aim of this paper is to propose a new mathematical model able to compute the electro-thermal performance of a Gate All Around (GAA)-FET transistors. The given electrical formulation is given by the Drift-Diffusion (D-D) model in conjunction with an effective electron mobility formulation. To better compute the nano heat conduction, the enhanced D-D model is coupled with the hydrodynamic model. To achieve high evidence to the proposed model, the simulation of the transfer and output characteristics are compared with experimental and numerical data, and we have succeeded to achieve a good concordance. Power dissipation with phonon radiation effect, device temperature has been studied in 50 nm and 10 nm of GAAFET gate lengths. We have shown that, the Joule effect increases with the decreases of the GAAFET gate length. On the other hand, we demonstrate that for the two studied structure, the saturated temperature from 360 K to 405 K when the device gate length increases from 10 nm to 50 nm, respectively. © 2023 IEEE.

关键词： Multiple-gate field-effect transistors

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Efficient Model-Based OPC via Graph Neural Network

Efficient Model-Based OPC via Graph Neural Network

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2023 International Symposium of Electronics Design Automation, ISEDA 2023

作者： Sun, Shuyuan Chen, Xuelian Yang, Fan Yu, Bei Li, Shang Zeng, Xuan School of Microelectronics Fudan University State Key Lab of ASIC and System China Cogenda Inc China The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350304510

As feature size continues to shrink and light source wavelengths remain unchanged, the optical diffraction effects seriously degrade chip yield. Optical proximity correction (OPC) has become an essential step for chip manufacturability. However, OPC cannot achieve satisfactory mask correction results in an affordable number of iterations on some layouts, delaying the chip design cycle. In this paper, we propose to use the Graph Neural Network (GNN) to predict the initial mask correction and speed up model-based OPC. We design a graph model to represent the chip layout, with segments represented as graph nodes and the diffraction effects between them represented as graph edges. The GNN is used to obtain the embedding of the segment, and we predict the shift value based on its output. The proposed GNN-based predictor enhances the original OPC to find a good correction solution for full-chip-size masks in fewer iterations. compared with the original OPC method, experimental results on 55nm and 32nm full chip designs show that the proposed GNN-based OPC method reduces the number of iterations up to 75% and the acquired mask of comparable quality. © 2023 IEEE.

关键词： Diffraction

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Electronics based on two-dimensional materials:Status and outlook

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Nano Research 2021年第6期14卷 1752-1767页

作者： Senfeng Zeng Zhaowu Tang Chunsen Liu Peng Zhou State Key Laboratory of ASIC and System School of MicroelectronicsFudan UniversityShanghai200433China School of Computer Science Fudan UniversityShanghai200433China

Since Moore’s law in the traditional semiconductor industry is facing shocks,More Moore and More than Moore are proposed as two paths to maintain the development of the semiconductor industry by adopting new architectures or new materials,in which the former is committed to the continued scaling of transistors for performance enhancement,and the latter pursues the realization of functional diversification of electronic ***-dimensional(2D)materials are supposed to play an important role in these two *** More Moore,the ultimate thin thickness and the dangling-bond-free surface of 2D channels offer excellent gate electrostatics while avoiding the degradation of carrier mobility at the same time,so that the transistors can be further scaled down for higher *** More than Moore,devices based on 2D materials can well meet the requirements of electronic systems for functional diversity,like that they can operate at high frequency,exhibit excellent sensitivity to the changes in the surroundings at room temperature,have good mechanical flexibility,and so *** this review,we present the application of 2D materials in More Moore and More than Moore domains of electronics,outlining their potential as a technological option for logic electronics,memory electronics,radio-frequency electronics,sensing electronics,and flexible electronics.

关键词： More Moore More Than Moore two-dimensional materials transition metal dichalcogenides(TMDs)

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Performance Assessment of a Modular Fault-Tolerant Multiphase Inverter

Performance Assessment of a Modular Fault-Tolerant Multiphas...

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2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2022

作者： Spampinato, Andrea Forte, Gianluigi Tornello, Luigi Danilo Scelba, Giacomo Scarcella, Giuseppe SRA-System Lab Development Unit St Microelectronics Catania Italy University of Catania Department of Electrical Electronics and Computer Engineering Catania Italy

ISBN: (数字)9781665484596

ISBN: (纸本)9781665484596

The main aim of this paper is to evaluate the performance of a modular fault-tolerant multiphase inverter prototype. Suitable current and voltage monitoring are implemented to maintain limited the electric and mechanical stresses during the fault detection, identification, and isolation phases. The realized fault-tolerant motor drive configuration covers different types of faults occurring in the power converter devices and the open-phase fault in the electric motor. The inverter has been tested on a six-phase induction motor prototype. © 2022 IEEE.

关键词： Fault detection

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Numerical Analysis of Self-Heating Effect in HEMT Transistors 4

Numerical Analysis of Self-Heating Effect in HEMT Transistor...

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4th International Conference on Electrical, Communication and computer Engineering, ICECCE 2023

作者： Nasri, Faouzi Mzoughi, Haikel Salama, Husien Salama, Khalifa Ahmed Center for Research in Microelectronics and Nanotechnology Sousse Tunisia Laboratory of thermal process Research and technology of energy Tunis Tunisia Computer System Institute Boston United States Libyan Center for Enginnering Research and Information Technology Bani Walid Libya

ISBN: (纸本)9798350369694

The analysis of power dissipation and operating temperature is of great importance for electrothermal design in power electronics. In this communication, an electrothermal simulation analysis of AlGaN/GaN double metal gate (DMG) high electron mobility transistor (HEMT) using finite element method (FEM) was done. The thermal and electrical behavior of the device was evaluated by simulating the output and transfer characteristics with and without Joule effect and power dissipation. In addition, we have carefully studied the effect of VDS drain polarization on the increase in the HEMT operating temperature. The results indicate that self-heating significantly degrades the electrical performance of the device, as evidenced by the increase in the operating temperature of the transistor. © 2023 IEEE.

关键词： High electron mobility transistors

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Polarization-induced photocurrent switching effect in heterojunction photodiodes

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Nano Research 2023年第4期16卷 5503-5510页

作者： Dingbo Chen Yu-Chang Chen Guang Zeng Yu-Chun Li Xiao-Xi Li Dong Li Chao Shen Nan Chi Boon S.Ooi David Wei Zhang Hong-Liang Lu State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics&SystemsSchool of MicroelectronicsFudan UniversityShanghai 200433China Key Laboratory for Information Science of Electromagnetic Waves Department of Communication Science and EngineeringFudan UniversityShanghai 200433China Photonics Laboratory Division of ComputerElectricaland Mathematical Sciences and EngineeringKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia

The unipolar photocurrent in conventional photodiodes(PDs)based on photovoltaic effect limits the output modes and potential versatility of these devices in *** photodiodes with photocurrent switching are emerging as a promising solution for obtaining photoelectric devices with unique and attractive functions,such as optical logic ***,we design an all-solid-state chip-scale ultraviolet(UV)PD based on a hybrid GaN heterojunction with engineered bipolar polarized electric *** introducing the polarization-induced photocurrent switching effect,the photocurrent direction can be switched in response to the wavelength of incident light at 0 V *** particular,the photocurrent direction exhibits negative when the irradiation wavelength is less than 315 nm,but positive when the wavelength is longer than 315 *** device shows a responsivity of up to−6.7 mA/W at 300 nm and 5.3 mA/W at 340 nm,*** particular,three special logic gates in response to different dual UV light inputs are demonstrated via a single bipolar PD,which may be beneficial for future multifunctional UV photonic integrated devices and systems.

关键词： GaN heterostructure ultraviolet(UV)photodiodes bipolar photocurrent optical logic device

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The Power of Graph Signal Processing for Chip Placement Acceleration 24

The Power of Graph Signal Processing for Chip Placement Acce...

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43rd International Conference on computer-Aided Design, ICCAD 2024

作者： Liu, Yiting Zhou, Hai Wang, Jia Yang, Fan Zeng, Xuan Shang, Li School of Computer Science Fudan University Shanghai China Department of ECE Northwestern University Evanston United States Department of ECE IIIinois Institute of Technology Chicago United States State Key Lab of ASIC & System Microelectronics Department Fudan University Shanghai China

ISBN: (纸本)9798400710773

Placement is a critical task with high computation complexity in VLSI physical design. Modern analytical placers formulate the placement objective as a nonlinear optimization task, which suffers a long iteration time. To accelerate and enhance the placement process, recent studies have turned to deep learning-based approaches, particularly leveraging graph convolution networks (GCNs). However, learning-based placers require time- and data-consuming model training due to the complexity of circuit placement that involves large-scale cells and design-specific graph statistics. This paper proposes GiFt, a parameter-free technique for accelerating placement, rooted in graph signal processing. GiFt excels at capturing multi-resolution smooth signals of circuit graphs to generate optimized placement solutions without the need for time-consuming model training, and meanwhile significantly reduces the number of iterations required by analytical placers. Experimental results show that GiFt significantly improving placement efficiency, while achieving competitive or superior performance compared to state-of-the-art placers. In particular, compared to DREAMPlace, the recently proposed GPU-accelerated analytical placer, GF-Placer improves total runtime over 45%. © 2024 Copyright is held by the owner/author(s).

关键词： Nonlinear programming

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A Programming Language Learning Service by Linking Stack Overflow with Textbooks

A Programming Language Learning Service by Linking Stack Ove...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Wu, Jiawei Sun, Yanchun Zhang, Jiaqi Zhou, Yuqi Huang, Gang Ministry of Education Key Laboratory of High Confidence Software Technologies China Peking University School of Computer Science Beijing China Peking University School of Software and Microelectronics Beijing China National Key Laboratory of Data Space Technology and System China

ISBN: (纸本)9798350304855

Before software developers actually start coding, an essential requirement is to be proficient in a programming language. However, as an important learning resource, programming language textbooks usually contain much about syntax and semantics of a programming language, but little about pragmatics, which is highly relevant with practical skills in solving real-world problems using programming languages. This makes it difficult for learners to transfer knowledge from textbooks to *** solve this problem, this paper proposes a programming language learning service, utilizing abundant development knowledge in Stack Overflow (SO) Q&A posts as the pragmatics knowledge of programming languages to make up for the shortage of pragmatics knowledge in textbooks. To link SO Q&A posts with textbooks, this paper first proposes a deep learning classification model to recognize SO posts containing development knowledge. Second, to align filtered SO posts with programming language learning processes, this paper proposes a weakly supervised link approach to matching SO posts with chapters and sections of textbooks. The feature of weak supervision ensures that the approach can be easily extended to other textbooks. Based on these modules above, this paper implements the programming language learning service in the form of a Chrome plugin. We conduct experiments and user study. Their results demonstrate the effectiveness, scalability and stability of the service. © 2023 IEEE.

关键词： Textbooks

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