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arXiv 2024年

作者： Zhang, Yue Zhang, Woyu Wang, Shaocong Lin, Ning Yu, Yifei He, Yangu Wang, Bo Jiang, Hao Lin, Peng Xu, Xiaoxin Qi, Xiaojuan Wang, Zhongrui Zhang, Xumeng Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100049 China ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong Institute of the Mind The University of Hong Kong Hong Kong Key Lab of Fabrication Technologies for Integrated Circuits Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai200433 China University of Chinese Academy of Sciences Beijing100049 China College of Computer Science and Technology Zhejiang University Zhejiang310027 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

The brain is dynamic, associative and efficient. It reconfigures by associating the inputs with past experiences, with fused memory and processing. In contrast, AI models are static, unable to associate inputs with past experiences, and run on digital computers with physically separated memory and processing. We propose a hardware-software co-design, a semantic memory-based dynamic neural network (DNN) using memristor. The network associates incoming data with the past experience stored as semantic vectors. The network and the semantic memory are physically implemented on noise-robust ternary memristor-based Computing-In-Memory (CIM) and Content-Addressable Memory (CAM) circuits, respectively. We validate our co-designs, using a 40nm memristor macro, on ResNet and PointNet++ for classifying images and 3D points from the MNIST and ModelNet datasets, which not only achieves accuracy on par with software but also a 48.1% and 15.9% reduction in computational budget. Moreover, it delivers a 77.6% and 93.3% reduction in energy consumption. © 2024, CC BY.

关键词： Memristors

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基于数据通路分片和冗余策略的片上容错路由器设计

基于数据通路分片和冗余策略的片上容错路由器设计

引用

第七届中国测试学术会议

作者： Lu Hang 路航 Han Yinhe 韩银和 Wang Ying 王颖 Li Xiaowei 李晓维 State Key Laboratory of Computer System and Architecture Chinese Academy of Sciences Beijing 10019 计算机系统结构国家重点实验室北京 100190 中国科学院计算技术研究所北京100190

为了满足系统芯片对通信带宽的要求,片上网络逐渐成为多核处理器互连的主流方案。然而随着集成电路技术进入纳米时代,由于制造缺陷、电粒子轰击等原因,片上网络出现故障的可能性明显增大,严重时会导致整个系统崩溃。以往的容错技术允许... 详细信息

为了满足系统芯片对通信带宽的要求,片上网络逐渐成为多核处理器互连的主流方案。然而随着集成电路技术进入纳米时代,由于制造缺陷、电粒子轰击等原因,片上网络出现故障的可能性明显增大,严重时会导致整个系统崩溃。以往的容错技术允许片上路由器分时复用其它正常工作的数据通路分片,以提高路由器的容错能力,降低传输延迟。然而,随着故障分片数量增多,路由器的可靠性和性能会受到严重影响。本文基于数据通路部件可分片的特点,对分片进行冗余备份,当分片出现故障时用冗余分片替代故障分片以提高路由器的可靠性。实验结果表明,本文提出的容错路由器硬件开销小于双模冗余,SPF达到12以上,当网络存在一定数量的故障时,仍有98％以上的节点可以正常工作。

关键词：集成电路片上网络容错路由器设计流程数据通路冗余备份

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Gaussian Boson Sampling with Pseudo-Photon-Number-Resolving Detectors and Quantum Computational Advantage

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Physical Review Letters 2023年第15期131卷 150601-150601页

作者： Yu-Hao Deng Yi-Chao Gu Hua-Liang Liu Si-Qiu Gong Hao Su Zhi-Jiong Zhang Hao-Yang Tang Meng-Hao Jia Jia-Min Xu Ming-Cheng Chen Jian Qin Li-Chao Peng Jiarong Yan Yi Hu Jia Huang Hao Li Yuxuan Li Yaojian Chen Xiao Jiang Lin Gan Guangwen Yang Lixing You Li Li Han-Sen Zhong Hui Wang Nai-Le Liu Jelmer J. Renema Chao-Yang Lu Jian-Wei Pan Hefei National Laboratory for Physical Sciences at Microscale and School of Physical Sciences University of Science and Technology of China Hefei Anhui 230026 China CAS Centre for Excellence and Synergetic Innovation Centre in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai 201315 China Hefei National Laboratory University of Science and Technology of China Hefei 230088 China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Micro system and Information Technology (SIMIT) Chinese Academy of Sciences 865 Changning Road Shanghai 200050 China Department of Computer Science and Technology and Beijing National Research Center for Information Science and Technology Tsinghua University Beijing 100084 China Adaptive Quantum Optics Group Mesa+ Institute for Nanotechnology University of Twente P.O. Box 217 7500 AE Enschede Netherlands New Cornerstone Science Laboratory Shenzhen 518054 China

We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for the characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and correlation function analysis to validate the samples against all current classical spoofing mockups. Estimating with the best classical algorithms to date, generating a single ideal sample from the same distribution on the supercomputer Frontier would take ∼600 yr using exact methods, whereas our quantum computer, Jiǔzhāng 3.0, takes only 1.27 μs to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier∼3.1×1010 yr.

关键词： Boson sampling Quantum computation Quantum information with atoms & light Quantum states of light Photon counting

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Model-driven deep learning for physical layer communications

arXiv

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arXiv 2018年

作者： He, Hengtao Jin, Shi Wen, Chao-Kai Gao, Feifei Li, Geoffrey Ye Xu, Zongben National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung804 Taiwan State Key Lab of Intelligent Technologies and Systems Tsinghua University Department of Automation Tsinghua University Beijing China School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Institute for Information and System Sciences Xian Jiaotong University Xi'an710049 China

Intelligent communication is gradually becoming a mainstream direction. As a major branch of machine learning, deep learning (DL) has been applied in physical layer communications and demonstrated an impressive performance improvement in recent years. However, most of the existing works related to DL focus on data-driven approaches, which consider the communication system as a black box and train it by using a huge volume of data. Training a network requires sufficient computing resources and extensive time, both of which are rarely found in communication devices. By contrast, modeldriven DL approaches combine communication domain knowledge with DL to reduce the demand for computing resources and training time. This article discusses the recent advancements in model-driven DL approaches in physical layer communications, including transmission schemes, receiver design, and channel information recovery. Several open issues for future research are also highlighted. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep learning

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The Age of Generative AI and AI-Generated Everything

arXiv

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arXiv 2023年

作者： Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Zhang, Ping Cui, Shuguang Shen, Xuemin Mao, Shiwen Han, Zhu Jamalipour, Abbas Vincent Poor, H. Kim, Dong In School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore School of Automation Guangdong University of Technology Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou510006 China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China Chinese University of Hong Kong Shenzhen China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Generative AI (GAI) has emerged as a significant advancement in artificial intelligence, renowned for its language and image generation capabilities. This paper presents "AIGenerated Everything" (AIGX), a concept that extends GAI beyond mere content creation to real-time adaptation and control across diverse technological domains. In networking, AIGX collaborates closely with physical, data link, network, and application layers to enhance real-time network management that responds to various system and service settings as well as application and user requirements. Networks, in return, serve as crucial components in further AIGX capability optimization through the AIGX lifecycle, i.e., data collection, distributed pre-training, and rapid decision-making, thereby establishing a mutually enhancing interplay. Moreover, we offer an in-depth case study focused on power allocation to illustrate the interdependence between AIGX and networking systems. Through this exploration, the article analyzes the significant role of GAI for networking, clarifies the ways networks augment AIGX functionalities, and underscores the virtuous interactive cycle they form. This article paves the way for subsequent future research aimed at fully unlocking the potential of GAI and networks. © 2023, CC BY.

关键词： Decision making

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Coalition game based user association for mmWave mobile relay systems in rail traffic scenarios

arXiv

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arXiv 2021年

作者： Chen, Chen Niu, Yong Mao, Shiwen Zhang, Xiaodan Han, Zhu Ai, Bo Gao, Meilin Xiao, Huahua Wang, Ning The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States The School of Management Shenzhen Institute of Information Technology Shenzhen518172 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China The Tsinghua Space Center Tsinghua University Beijing100091 China The ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China

Rail transportation, especially, high-speed rails (HSR), is an important infrastructure for the development of national economy and the promotion of passenger experience. Due to the large bandwidth, millimeter wave (mmWave) communication is regarded as a promising technology to meet the demand of high data rates. However, since mmWave communication has the characteristic of high attenuation, mobile relay (MR) is considered in this paper. Also, full-duplex (FD) communications have been proposed to improve the spectral efficiency. However, because of the high speed, as well as the problem of penetration loss, passengers on the train have a poor quality of service. Consequently, an effective user association scheme for HSR in mmWave band is necessary. In this paper, we investigate the user association optimization problem in mmWave mobile relay systems where the MRs operate in the FD mode. To maximize the system capacity, we propose a cooperative user association approach based on coalition formation game, and develop a coalition formation algorithm to solve the challenging NP-hard problem. We also prove the convergence and Nash-stable property of the proposed algorithm. Extensive simulations are done to show the system performance of the proposed scheme under various network settings. It is demonstrated that the proposed distributed low complexity scheme achieves a near-optimal performance and outperforms two baseline schemes in terms of average system throughput. Copyright © 2021, The Authors. All rights reserved.

关键词： Game theory

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Robust trajectory and transmit power optimization for secure UAV-enabled cognitive radio networks

arXiv

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arXiv 2020年

作者： Zhou, Yifan Zhou, Fuhui Zhou, Huilin Kwan Ng, Derrick Wing Qingyang Hu, Rose School of Information Engineering Nanchang University Nanchang330031 China College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing210000 China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space [Nanjing University of Aeronautics and Astronautics Ministry of Industry and Information Technology Nanjing211106 China Department of Electrical and Computer Engineering Utah State University LoganUT84322 United States University of New South Wales SydneyNSW2052 Australia

Cognitive radio is a promising technology to improve spectral efficiency. However, the secure performance of a secondary network achieved by using physical layer security techniques is limited by its transmit power and channel fading. In order to tackle this issue, a cognitive unmanned aerial vehicle (UAV) communication network is studied by exploiting the high flexibility of a UAV and the possibility of establishing line-of-sight links. The average secrecy rate of the secondary network is maximized by robustly optimizing the UAV’s trajectory and transmit power. Our problem formulation takes into account two practical inaccurate location estimation cases, namely, the worst case and the outage-constrained case. In order to solve those challenging non-convex problems, an iterative algorithm based on S-Procedure is proposed for the worst case while an iterative algorithm based on Bernstein-type inequalities is proposed for the outage-constrained case. The proposed algorithms can obtain effective suboptimal solutions of the corresponding problems. Our simulation results demonstrate that the algorithm under the outage-constrained case can achieve a higher average secrecy rate with a low computational complexity compared to that of the algorithm under the worst case. Moreover, the proposed schemes can improve the secure communication performance significantly compared to other benchmark schemes. Copyright © 2020, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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基于深度学习技术的集群电动汽车及家庭热水系统灵活性预测

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Engineering 2021年第8期7卷 141-169页

作者：胡俊杰周华嫣然周羿宏张海婧 Lars Nordstr?md 杨光亚 State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University) Division of Electric Power and Energy Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Center for Electric Power and Energy Department of Electrical Engineering Technical University of Denmark

随着电网中间歇性可再生能源发电规模的增大，为了保证电能质量和频率的稳定性，电网对可控资源的需求也随之增加。需求响应（demand response, DR）资源的灵活性已成为解决这一问题的一个有价值的方法。然而，目前关于DR资源的灵活性... 详细信息

随着电网中间歇性可再生能源发电规模的增大，为了保证电能质量和频率的稳定性，电网对可控资源的需求也随之增加。需求响应（demand response, DR）资源的灵活性已成为解决这一问题的一个有价值的方法。然而，目前关于DR资源的灵活性预测问题尚未得到充分的研究。本研究应用一种深度学习技术，即结合时间卷积神经网络的TRANSFORMER模型（temporal convolution network-combined transformer）来预测电动汽车与家庭热水系统两种DR资源的聚合灵活性。所提出的灵活性预测方法使用了基于DR资源的历史用电数据以及为了辅助预测所提出的DR信号数据。所提方法不仅可以预测聚合灵活性的大小，还可以预测其维持时间。最后，本文通过算例仿真验证了灵活性预测结果的准确性。仿真结果表明，在不同的灵活性维持时间下，DR资源灵活性的大小会发生变化。文中所提出的DR资源灵活性预测方法展现了其在释放需求侧资源的灵活性以向电网提供备用容量方面的应用。

关键词：负荷灵活性电动汽车家庭热水系统结合时间卷积神经网络的Transformer模型深度学习

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Pointwise Logic on Completely Distributive Lattices and Approximate Reasoning

Pointwise Logic on Completely Distributive Lattices and Appr...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Yalin Zheng Guang Yang Jing Zheng Jinsheng Xing State Key Laboratory for Intelligent Technology and Systems Department of Automation Faculty of Information Science and Technology Tsinghua University Beijing China Research Center of Intelligent Information Technology Department of Computer Science and Technology Faculty of Software Dongguan University of Science and Technology Dongguan China Research Center of Dongguan Economy Department of Economy and Commerce Dongguan University of Science and Technology Dongguan China Faculty of Mathematics and Computer Science Shanxi Normal University Linfen China Research Center of System Engineering Faculty of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China

In this paper, we propose the basic framework of point- wise topological logic on completely distributive lattices and explore approximate reasoning in it. The logic of this paper is based on pointwise characterization, therefore the pointwise conception is pervasive. We explore approximate reasoning in abstract logical framework Fl on completely distributive lattice L. We propose the structure of point- wise topological logic F TL , the structure of matching function sigma. and the structure of matching neighborhood group. We investigate approximate reasoning in pointwise topological logic F TL with matching function sigma, develop pointwise topological algorithm of simple approximate reasoning, introduce the essential characteristics of this scheme.

关键词： Lattices Fuzzy logic computer science Knowledge engineering Fuzzy systems Information technology Laboratories Intelligent systems Automation Information science

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The influence of high-energy local orbitals and electron-phonon interactions on the band gaps and optical spectra of hexagonal boron nitride

arXiv

引用

arXiv 2020年

作者： Shen, Tong Zhang, Xiao-Wei Shang, Honghui Zhang, Min-Ye Wang, Xinqiang Wang, En-Ge Jiang, Hong Li, Xin-Zheng State Key Laboratory for Artificial Microstructure and Mesoscopic Physics Frontier Science Center for Nano-optoelectronics School of Physics Peking University Beijing China International Center for Quantum Materials and School of Physics Peking University Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China Beijing National Laboratory for Molecular Sciences College of Chemistry and Molecular Engineering Peking University Beijing China Collaborative Innovation Center of Quantum Matter Peking University Beijing100871 China Ceramic Division Songshan Lake Lab Institute of Physics Chinese Academy of Sciences Guangdong China School of Physics Liaoning University Shenyang China Beijing National Laboratory for Molecular Sciences College of Chemistry and Molecular Engineering Peking University Beijing China Collaborative Innovation Center of Quantum Matter Peking University Beijing China

We report ab initio band diagram and optical absorption spectra of hexagonal boron nitride (h-BN), focusing on unravelling how the completeness of basis set for GW calculations and how electron-phonon interactions (EPIs) impact on them. The completeness of basis set, an issue which was seldom discussed in previous optical spectra calculations of h-BN, is found crucial in providing converged quasiparticle band gaps. In the comparison among three different codes, we demonstrate that by including high-energy local orbitals in the all-electron linearized augmented plane waves based GW calculations, the quasiparticle direct and fundamental indirect band gaps are widened by ∼0.2 eV, giving values of 6.81 eV and 6.25 eV respectively at the GW0 level. EPIs, on the other hand, reduce them to 6.62 eV and 6.03 eV respectively at 0 K, and 6.60 eV and 5.98 eV respectively at 300 K. With clamped crystal structure, the first peak of the absorption spectrum is at 6.07 eV, originating from the direct exciton contributed by electron transitions around K in the Brillouin zone. After including the EPIs-renormalized quasiparticles in the Bethe-Salpeter equation, the exciton-phonon coupling shifts the first peak to 5.83 eV at 300 K, lower than the experimental value of ∼6.00 eV. This accuracy is acceptable to an ab initio description of excited states with no fitting parameter. Copyright © 2020, The Authors. All rights reserved.

关键词： III-V semiconductors

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