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A new metric for ranking high-performance computing systems

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National Science Review 2016年第1期3卷 30-35页

作者： Jack Dongarra Michael A.Heroux Piotr Luszczek Innovative Computing Laboratory EECS DepartmentUniversity of Tennessee

INTRODUCTION Performance benchmarks play an important role in various stages of hardware development and *** development,hardware designers use benchmarks as proxies for full-fledged applications because prototype sys... 详细信息

关键词： code A new metric for ranking high-performance computing systems PDEs NPB high

Sunway Taihu Light supercomputer makes its appearance

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National Science Review 2016年第3期3卷 265-266页

作者： Jack Dongarra Innovative Computing Laboratory EECS DepartmentUniversity of Tennessee

The Sunway Taihu Light System[1] is very impressive with over 10 million cores and a peak performance of just over 125 Pflop/*** Top500 list has the Sunway Taihu Light as the fastest *** Sunway is almost three times(2... 详细信息

关键词： Bell Sunway Taihu Light supercomputer makes its appearance high ACC

BSIM--making the first international standard MOSFET model

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Science in China(Series F) 2008年第6期51卷 765-773页

作者： HU ChenMing department of eecs University of California at Berkeley CA 94720 USA

BSIM （Berkeley Short-Channel IGFET） became the first international industry standard model for simulation of MOS integrated circuits in 1997. The cumulative sales of ICs that have been designed with the aid of BSIM and produced for computing, communication, consumer, and industrial applications is estimated to be around 400 billion US dollars. From 0.35μm CMOS to multi-gate FinFET, BSIM serves a wide range of technologies. Many China educated researchers have contributed to its success.

关键词： BSIM MOS compact modeling

Flexible Global Aggregation and Dynamic Client Selection for Federated Learning in Internet of Vehicles

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Computers, Materials & Continua 2023年第11期77卷 1739-1757页

作者： Tariq Qayyum Zouheir Trabelsi Asadullah Tariq Muhammad Ali Kadhim Hayawi Irfan Ud Din College of Information Technology United Arab Emirates UniversityAl Ain17551UAE department of Computing School of EECSNational University of Sciences and TechnologyIslamabad44000Pakistan College of Technological Innovation Zayed UniversityAbu Dhabi144534UAE department of Computer Science The Superior UniversityLahore54000Pakistan

Federated Learning(FL)enables collaborative and privacy-preserving training of machine learning models within the Internet of Vehicles(IoV)*** FL effectively tackles privacy concerns,it also imposes significant resource *** traditional FL,trained models are transmitted to a central server for global aggregation,typically in the *** approach often leads to network congestion and bandwidth limitations when numerous devices communicate with the same *** need for Flexible Global Aggregation and Dynamic Client Selection in FL for the IoV arises from the inherent characteristics of IoV *** include diverse and distributed data sources,varying data quality,and limited communication *** employing dynamic client selection,we can prioritize relevant and high-quality data sources,enhancing model *** address this issue,we propose an FL framework that selects global aggregation nodes dynamically rather than a single fixed *** global aggregation ensures efficient utilization of limited network resources while accommodating the dynamic nature of IoV data *** approach optimizes both model performance and resource allocation,making FL in IoV more effective and *** selection of the global aggregation node is based on workload and communication speed ***,our framework overcomes the constraints associated with network,computational,and energy resources in the IoV environment by implementing a client selection algorithm that dynamically adjusts participants according to predefined *** approach surpasses Federated Averaging(FedAvg)and Hierarchical FL(HFL)regarding energy consumption,delay,and accuracy,yielding superior results.

关键词： IoT Federated Learning sensors IoV OMNeT++ edge computing

Virtual screening of inorganic materials synthesis parameters with deep learning

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npj Computational Materials 2017年第1期3卷 14-22页

作者： Edward Kim Kevin Huang Stefanie Jegelka Elsa Olivetti department of Materials Science and Engineering MITCambridgeMAUSA department of eecs and CSAIL MITCambridgeMAUSA

Virtual materials screening approaches have proliferated in the past decade,driven by rapid advances in first-principles computational techniques,and machine-learning *** comparison,computationally driven materials synthesis screening is still in its infancy,and is mired by the challenges of data sparsity and data scarcity:Synthesis routes exist in a sparse,highdimensional parameter space that is difficult to optimize over directly,and,for some materials of interest,only scarce volumes of literature-reported syntheses are *** this article,we present a framework for suggesting quantitative synthesis parameters and potential driving factors for synthesis *** use a variational autoencoder to compress sparse synthesis representations into a lower dimensional space,which is found to improve the performance of machine-learning *** realize this screening framework even in cases where there are few literature data,we devise a novel data augmentation methodology that incorporates literature synthesis data from related materials *** apply this variational autoencoder framework to generate potential SrTiO_(3) synthesis parameter sets,propose driving factors for brookite TiO_(2) formation,and identify correlations between alkali-ion intercalation and MnO_(2) polymorph selection.

关键词： synthesis variational inorganic

Hybrid component and configuration model for combined-cycle units in unit commitment problem

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Journal of Modern Power Systems and Clean Energy 2018年第6期6卷 1332-1337页

作者： Xin FANG Linquan BAI Fangxing LI Bri-Mathias HODGE National Renewable Energy Laboratory ABB Inc. department of eecs The University of Tennessee

This letter proposes a novel hybrid component and configuration model for combined-cycle gas turbines(CCGTs) participating in independent system operator(ISO) markets. The proposed model overcomes the inaccuracy issues in the current configuration-based model while retaining its simple and flexible bidding framework of configuration-based models. The physical limitations—such as minimum online/offline time and ramping rates—are modeled for each component separately, and the cost is calculated with the bidding curves from the configuration modes. This hybrid mode can represent the current dominant bidding model in the unit commitment problem of ISOs while treating the individual components in CCGTs accurately. The commitment status of the individual components is mapped to the unique configuration mode of the CCGTs. The transitions from one configuration mode to another are also modeled. No additional binary variables are added, and numerical case studies demonstrate the effectiveness of this model for CCGT units in the unit commitment problem.

关键词： Combined-cycle gas turbines(CCGTs) Unit commitment Component-based model Configurationbased model

Building the metaverse using digital twins at all scales,states,and relations

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Virtual Reality & Intelligent Hardware 2022年第6期4卷 459-470页

作者： Zhihan LV Shuxuan XIE Yuxi LI M.Shamim HOSSAIN Abdulmotaleb El SADDIK department of Game Design Faculty of ArtsUppsala UniversitySweden College of Computer Science and Technology Qingdao UniversityQingdaoChina department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia School of Electrical Engineering and Computer Science(eecs) University of OttawaOttawaOntarioCanada

Developments in new-generation information technology have enabled Digital Twins to reshape the physical world into a virtual digital space and provide technical support for constructing the *** objects can be at the micro-,meso-,or *** Metaverse is a complex collection of solid,liquid,gaseous,plasma,and other uncertain ***,the Metaverse integrates tangibles with social relations,such as interpersonal(friends,partners,and family)and social relations(ethics,morality,and law).This review introduces some principles and laws,such as broken windows theory,small-world phenomenon,survivor bias,and herd behavior,for constructing a Digital Twins model for social ***,from multiple perspectives,this article reviews mappings of tangible and intangible real-world objects to the Metaverse using the Digital Twins model.

关键词： Digital twins Metaverse Sensor

Generating Basic Unit Movements with Conditional Generative Adversarial Networks

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Chinese Journal of Electronics 2019年第6期28卷 1099-1107页

作者： LUO Dingsheng NIE Mengxi WU Xihong Key Laboratory of Machine Perception (Ministry of Education) Speech and Hearing Research CenterDepartment of Machine Intelligence School of EECS Peking University

Arm motion control is fundamental for robot accomplishing complicated manipulation *** movements can be organized by configuring a series of motion units. Our work aims at equipping the robot with the ability to carry out Basic unit movements(BUMs), which are used to constitute various motion sequences so that the robot can drive its hand to a desired position. With the definition of BUMs, we explore a learning approach for the robot to develop such an ability by leveraging deep learning technique. In order to generate the BUM regarding to the current arm state,an internal inverse model is developed. We propose to use Conditional generative adversarial networks(CGANs) to establish the inverse model to generate the BUMs. The experimental results on a humanoid robot PKU-HR6.0Ⅱ illustrate that CGANs could successfully generate multiple solutions given a BUM, and these BUMs can be used to constitute further reaching movement effectively.

关键词： Arm motion control Basic unit movements Deep learning CGANs Inverse model Humanoids

Modeling of subthreshold characteristics for undoped and doped deep nanoscale short channel double-gate MOSFETs

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Journal of Semiconductors 2012年第12期33卷 27-30页

作者：靳晓诗刘溪吴美乐揣荣岩 Jung-Hee Lee Jong-Ho Lee School of Information Science and Engineering Shenyang University of Technology School of eecs Kyungpook National University School of eecs Eng.and ISRC(Inter-University Semiconductor Research Center) Seoul National University

A model of subthreshold characteristics for both undoped and doped double-gate （DG） MOSFETs has been proposed. The models were developed based on solution of 2-D Poisson＇s equation using variable separa- tion technique. Without any fitting parameters, our proposed models can exactly reflect the degraded subthreshold characteristics due to nanoscale channel length. Also, design parameters such as body thickness, gate oxide thick- ness and body doping concentrations can be directly reflected from our models. The models have been verified by comparing with device simulations＇ results and found very good agreement.

关键词： double-gate MOSFETs deep nanoscale modeling