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Computing-centric computing-in-memory and memory-centric in-/near-memory computing for DNNs and transformer based LLMs 认领 引用
1
作者 Xin Si Xing Wang Jun Yang 《Journal of Semiconductors》 EI CAS CSCD 2026年第7期7-11,共5页
Introduction.With the rapid development of transformer-based large language models(LLMs)and deep neural networks(DNNs),the demand for both high computational throughput and massive memory capacity has grown exponentia... Introduction.With the rapid development of transformer-based large language models(LLMs)and deep neural networks(DNNs),the demand for both high computational throughput and massive memory capacity has grown exponentially[1-4].In response,the 2D/3D hybrid integration of computing-centric computing-in-memory(CIM)and memory-centric in-ear-memory computing(INMC)circuits has emerged as a transformative technology.Unlike conventional von Neumann architectures,these memory-computing hybrid designs offer systematic advantages including high energy efficiency,high memory bandwidth,and sufficient on-device memory capacity[1-13]. 展开更多
关键词 von neumann architecturesthese near memory computing transformer based large language models large language models llms memory computing deep neural networks dnns memory centric computing centric
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Large-scale integrated photonic accelerators for ultralow-latency and universal AI computing 认领 引用
2
作者 Xiangyan Meng Junshen Li +4 位作者 Kangwei Fei Yu Wang Wei Li Nuannuan Shi Ming Li 《Journal of Semiconductors》 EI CAS CSCD 2026年第6期12-15,共4页
Integrated silicon photonics has emerged as a transformative technology for post-Moore’s law computing,offering intrinsic advantages of high bandwidth,ultralow latency and low energy consumption that far exceed tradi... Integrated silicon photonics has emerged as a transformative technology for post-Moore’s law computing,offering intrinsic advantages of high bandwidth,ultralow latency and low energy consumption that far exceed traditional electronic computing architectures[1−4].As artificial intelligence(AI)models continue to grow in complexity and scale,the demand for high-speed,energy-efficient computing has spurred intensive research into photonic computing as a promising alternative to electronic accelerators[5−7].Matrix multiply−accumulate(MAC)operations,the core of deep learning and combinatorial optimization algorithms,are particularly amenable to photonic implementation,as light enables parallel multiplication and accumulation with minimal data movement[8,9].However,the practical application of photonic computing has long been hindered by critical challenges including large-scale integration of photonic components,electro-optical co-packaging,guaranteed computation accuracy of analog photonic systems,and compatibility with mainstream AI models and algorithms[10,11]. 展开更多
关键词 photonic computing integrated silicon photonics electronic computing ultralow latency matrix multiply accumulate analog photonic systems silicon photonics electronic accelerators matrix
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Introduction to the Special Issue on Next-Generation Intelligent Networks and Systems:Advances in IoT,Edge Computing,and Secure Cyber-Physical Applications 认领 引用
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作者 Nishu Gupta Manuel J.C.S.Reis 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期25-28,共4页
The accelerating convergence of intelligent networking paradigms,data-driven modeling,and cyberphysical integration is reshaping the foundations of modern engineering systems.Within this context,this Special Issue of ... The accelerating convergence of intelligent networking paradigms,data-driven modeling,and cyberphysical integration is reshaping the foundations of modern engineering systems.Within this context,this Special Issue of Computer Modeling in Engineering&Sciences(CMES)is devoted to recent advances in next-generation intelligent networks and systems,with a particular emphasis on the synergistic roles of the Internet of Things(IoT),edge computing,and secure cyber-physical applications. 展开更多
关键词 intelligent networking paradigmsdata driven computer modeling internet things edge computing intelligent networking paradigms cyberphysical integration internet things iot edge computingand data driven modeling
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Introduction to the Special Issue on Scientific Computing and Its Application to Engineering Problems 认领 引用
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作者 Higinio Ramos M Chandru 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期22-24,共3页
Scientific computing has become a cornerstone of modern scientific discovery and engineering innovation.With the rapid advancement of computational power and numerical algorithms,problems that were once analytically i... Scientific computing has become a cornerstone of modern scientific discovery and engineering innovation.With the rapid advancement of computational power and numerical algorithms,problems that were once analytically intractable can now be studied through accurate simulations and large-scale numerical experiments.Scientific computing provides a bridge between mathematical theory,computational algorithms,and real-world engineering applications,enabling researchers to model complex phenomena such as fluid flow,structural deformation,wave propagation,stochastic processes,and nonlinear dynamical systems.The special issue entitled“Scientific Computing and Its Application to Engineering Problems”was conceived to bring together high-quality research contributions that demonstrate the role of computational mathematics in solving challenging engineering problems.The issue highlights both theoretical advances in numerical methods and their practical deployment in real-world engineering scenarios,with emphasis on robustness,computational efficiency,stability,and scalability. 展开更多
关键词 scientific computing accurate simulations fluid flows numerical algorithmsproblems computational power numerical algorithms engineering problems model complex phenomena
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Intelligent Reconfigurable Skyrmion-Based Multi-Port Logic Device for In-Memory Computing 认领 引用
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作者 Fuhao Zou Ziyuan Liu +3 位作者 Zijing Zhao Muhammad Humayun Chundong Wang Xiaolei Wang 《Chinese Physics Letters》 SCIE EI CAS CSCD 2026年第3期331-345,共15页
New electronic devices based on the physical properties of electrically driven skyrmions are promising for logic computing and nonvolatile memory applications.However,achieving efficient and practical compute-storage ... New electronic devices based on the physical properties of electrically driven skyrmions are promising for logic computing and nonvolatile memory applications.However,achieving efficient and practical compute-storage integration remains challenging owing to the structural complexity,limited functionality,and low flexibility observed in most skyrmion-based devices.In this study,we designed a novel device architecture that integrates seven basic logic gates into a unified physical structure.Their operation can be enabled by physical mechanisms,such as spin-orbit torque,spin-transfer torque,skyrmion-edge repulsions,and skyrmion-skyrmion interactions.Furthermore,by incorporating voltage-controlled magnetic anisotropy,the device achieved multi-input capability and reconfigurability functionality.Ultralow power consumption(<1 fJ/bit per logic function)and extremely high logic density were achieved.Significantly,the compatibility of this nanotrack design with existing skyrmion racetrack memory paves the way for advanced in-memory computing in spintronic architectures. 展开更多
关键词 voltage controlled magnetic anisotropy intelligent reconfigurable skyrmion based multi port logic device memory computing logic computing device architecture spin transfer torque spin orbit torque integrates seven basic logic gates
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Toward wafer-level packaged high-speed photodetectors for AI computing interconnects 认领 引用
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作者 Di Liang 《Advanced Photonics Nexus》 CSCD 2026年第3期3-4,共2页
The explosive growth of artificial intelligence(AI)computing,particularly large-scale model training and inference in GPU and accelerator clusters,is driving unprecedented demand for interconnects that deliver high ba... The explosive growth of artificial intelligence(AI)computing,particularly large-scale model training and inference in GPU and accelerator clusters,is driving unprecedented demand for interconnects that deliver high bandwidth,low latency,and strong energy efficiency.As electrical links increasingly run into limits in bandwidth density,power consumption,and signal integrity,optical interconnects have emerged as a key enabling technology for next-generation AI systems.In this context,continued scaling of co-packaged optics and wafer-level photonic integration will require not only high-speed photodetectors,but also manufacturable packaging solutions that can support massive parallel optical input/output(I/O)at lower cost and power. 展开更多
关键词 photonic integration co packaged optics interconnects electrical links model training wafer level packaging gpu accelerator clustersis AI computing
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Task Offloading and Edge Computing in IoT-Gaps, Challenges and Future Directions 认领 引用 被引量：1
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作者 Hitesh Mohapatra 《Computers, Materials & Continua》 SCIE EI 2026年第6期268-296,共29页
This review examines current approaches to real-time decision-making and task optimization in Internet of Things systems through the application of machine learning models deployed at the network edge.Existing literat... This review examines current approaches to real-time decision-making and task optimization in Internet of Things systems through the application of machine learning models deployed at the network edge.Existing literature shows that edge-based distributed intelligence reduces cloud dependency.It addresses transmission latency,device energy use,and bandwidth limits.Recent optimization strategies employ dynamic task offloading mechanisms to determine optimal workload placement across local devices and edge servers without centralized coordination.Empirical findings from the literature indicate performance improvements with latency reductions of approximately 32.8%and energy efficiency gains of 27.4%compared to conventional cloud-centric models.However,critical gaps remain in current methodologies.Most studies focus on static network topologies and do not adequately address load balancing across multiple edge nodes.Security vulnerabilities during task transmission are underexplored,and privacy considerations for sensitive data remain insufficiently integrated into existing frameworks.Task caching strategies and fault tolerance mechanisms require further investigation in highly dynamic environments.The ability of existing approaches to handle large-scale deployments and complex edge-cloud collaborative scenarios has not been thoroughly validated.This review synthesizes current progress while identifying fundamental challenges that must be resolved for practical deployment in time-sensitive applications spanning smart manufacturing,autonomous systems,and healthcare monitoring.Future work should prioritize robust security integration,efficient load distribution,and scalability across heterogeneous edge infrastructures. 展开更多
关键词 Edge computing task offloading deep reinforcement learning mobile edge computing IoT performance optimization methodological rigor assessment
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Monitoring and Observability in Edge Computing Systems: Taxonomy, Comparative Analysis, and Research Directions 认领 引用
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作者 Hamza Ahmed Hassan Jamil Syed +3 位作者 Aqsa Aslam Sehar Zehra Ummay Faseeha Nurzati Iwani Othman 《Computers, Materials & Continua》 SCIE EI 2026年第8期165-196,共32页
Edge computing is an emerging model for latency-sensitive and distributed applications.However,the observability of edge computing systems in heterogeneous environments remains a challenge,as most existing approaches ... Edge computing is an emerging model for latency-sensitive and distributed applications.However,the observability of edge computing systems in heterogeneous environments remains a challenge,as most existing approaches are limited to only the system,service,application,and network layers.This paper surveys state-of-the-art solutions for edge observability and monitoring.The paper further introduces a thematic taxonomy that groups the state-of-the-art edge observability and monitoring literature based on monitoring intent,telemetry indicators,observability scope,architectural layers,deployment environments,and observability toolchains.Finally,we compare representative solutions in terms of latency,system overhead,bandwidth consumption,and detection accuracy.Our analysis reveals the trade-offs present in existing solutions regarding the overhead and performance metrics,as well as the limitations they impose when scaling,addressing mobility,or augmenting telemetry.Lastly,we conclude with a discussion on open challenges and future directions for designing next-generation,edge observability frameworks. 展开更多
关键词 Edge computing edge monitoring monitoring solutions observability telemetry microservices performance analysis distributed systems
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LLM-Enhanced Multi-Agent Transfer Reinforcement Learning for Sensing,Communication,Computing,and Control Co-Optimization in Cyber-Physical Systems 认领 引用
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作者 Junyuan Zhang Chi Xu Haibin Yu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第5期1251-1253,共3页
Dear Editor,With the rapid development of new-generation information and communication technology,the fusion of sensing,communication,computing,and control(S3C)is becoming increasingly significant for cyber-physical s... Dear Editor,With the rapid development of new-generation information and communication technology,the fusion of sensing,communication,computing,and control(S3C)is becoming increasingly significant for cyber-physical systems(CPS).However,due to the non-convexity,the curse of dimensionality,and the partial observability faced by CPS,traditional convex optimization algorithms are challenging to deal with S3C co-optimization. 展开更多
关键词 computing convex optimization algorithms LLM enhanced reinforcement communication sensing learning multi agent
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A Review of Next-Generation Smart Manufacturing Enabled by Engineering Systems,Materials Modeling,and High-Performance Computing:A System-Oriented Perspective for Semiconductor Manufacturing 认领 引用
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作者 Hsiao-Chun Han Der-Chen Huang Chin-Ling Chen 《Computers, Materials & Continua》 SCIE EI 2026年第10期307-404,共98页
Semiconductors represent the most complex production activities and stand at the forefront of smart manufacturing.In particular,the yield of advanced processes is strongly influenced by coupling among engineering syst... Semiconductors represent the most complex production activities and stand at the forefront of smart manufacturing.In particular,the yield of advanced processes is strongly influenced by coupling among engineering systems,material behavior,and computational infrastructure.Consequently,the integration of deep learning(DL)and digital twins has become essential for driving the next-generation transformation of smart manufacturing.However,existing reviews predominantly organize literature through algorithm-oriented taxonomies,while isolated AI paradigms alone remain insufficient to effectively capture system-level interactions and industry-driven technological evolution.Therefore,this study proposes a system-oriented and industry-driven review framework,termed the System-under-Industry Guided Literature Review(SIGLR),to reorganize existing literature.Specifically,103 survey papers and the 13,377 studies they reference are systematically analyzed.In addition,a triadic ESA-MM-HPC framework is introduced as a system-oriented conceptual representation for analyzing next-generation semiconductor smart manufacturing systems,capturing the coupling among engineering system analysis(ESA),material modeling(MM),and high-performance computing(HPC)in complex manufacturing environments.Furthermore,a conceptual modeling perspective is proposed for predictive digital twin(DT)analysis.Overall,this study uses the semiconductor industry as a representative domain to extend existing smart manufacturing research from algorithm-centered approaches toward more system-and structure-oriented perspectives.The perspectives provide a unified,scalable foundation for AI-driven industrial systems research,advancing manufacturing technologies and discussing challenges associated with globally distributed semiconductor manufacturing and industrial reshoring. 展开更多
关键词 Engineering system analysis material modeling high performance computation digital twin smart manufacturing semiconductor TSMC automatic control systems robotic manipulators automated guided vehicles
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Computing power networks for unmanned aerial vehicles:a hierarchical resources trading market 认领 引用
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作者 Xiaofei Wang Hui Deng +3 位作者 Chao Qiu Zheyuan Chen Tao Luo Zhao Ming 《Digital Communications and Networks》 SCIE EI CSCD 2026年第4期584-593,共10页
Unmanned Aerial Vehicles(UAVs)are increasingly deployed across military and civilian domains due to their operational flexibility,low maintenance costs,and high mobility.With the growing complexity of UAV applications... Unmanned Aerial Vehicles(UAVs)are increasingly deployed across military and civilian domains due to their operational flexibility,low maintenance costs,and high mobility.With the growing complexity of UAV applications and tasks,robust support from computing power networks is essential.These networks,acting as resource integration paradigms,furnish UAVs with pooled resources to tackle extensive computational demands.In this paper,we develop a framework for trading computing power resources,modeling the transaction process through a three-stage Stackelberg game to facilitate sequential decision-making.We theoretically demonstrate the existence of a Nash equilibrium and introduce a Dynamic Game Reinforcement algorithm to identify optimal strategies.Our experimental results affirm the framework's efficacy and the superior performance of our algorithm.Additionally,we explore how variables like UAV quantity and network congestion influence the market dynamics of the computing power network. 展开更多
关键词 UAVs Cloud computing Computing power network Resource trading Stackelberg game
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Back-gate-tuned organic electrochemical transistor with temporal dynamic modulation for reservoir computing 认领 引用
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作者 Qian Xu Jie Qiu +6 位作者 Mengyang Liu Dongzi Yang Tingpan Lan Jie Cao Yingfen Wei Hao Jiang Ming Wang 《Journal of Semiconductors》 EI CAS CSCD 2026年第1期118-123,共6页
Organic electrochemical transistor(OECT)devices demonstrate great promising potential for reservoir computing(RC)systems,but their lack of tunable dynamic characteristics limits their application in multi-temporal sca... Organic electrochemical transistor(OECT)devices demonstrate great promising potential for reservoir computing(RC)systems,but their lack of tunable dynamic characteristics limits their application in multi-temporal scale tasks.In this study,we report an OECT-based neuromorphic device with tunable relaxation time(τ)by introducing an additional vertical back-gate electrode into a planar structure.The dual-gate design enablesτreconfiguration from 93 to 541 ms.The tunable relaxation behaviors can be attributed to the combined effects of planar-gate induced electrochemical doping and back-gateinduced electrostatic coupling,as verified by electrochemical impedance spectroscopy analysis.Furthermore,we used theτ-tunable OECT devices as physical reservoirs in the RC system for intelligent driving trajectory prediction,achieving a significant improvement in prediction accuracy from below 69%to 99%.The results demonstrate that theτ-tunable OECT shows a promising candidate for multi-temporal scale neuromorphic computing applications. 展开更多
关键词 neuromorphic computing reservoir computing OECT tunable dynamics trajectory prediction
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Multi-Objective Enhanced Cheetah Optimizer for Joint Optimization of Computation Offloading and Task Scheduling in Fog Computing 认领 引用
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作者 Ahmad Zia Nazia Azim +5 位作者 Bekarystankyzy Akbayan Khalid J.Alzahrani Ateeq Ur Rehman Faheem Ullah Khan Nouf Al-Kahtani Hend Khalid Alkahtani 《Computers, Materials & Continua》 SCIE EI 2026年第3期1559-1588,共30页
The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous c... The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous computing networks.Finding an optimal computational resource for task offloading and then executing efficiently is a critical issue to achieve a trade-off between energy consumption and transmission delay.In this network,the task processed at fog nodes reduces transmission delay.Still,it increases energy consumption,while routing tasks to the cloud server saves energy at the cost of higher communication delay.Moreover,the order in which offloaded tasks are executed affects the system’s efficiency.For instance,executing lower-priority tasks before higher-priority jobs can disturb the reliability and stability of the system.Therefore,an efficient strategy of optimal computation offloading and task scheduling is required for operational efficacy.In this paper,we introduced a multi-objective and enhanced version of Cheeta Optimizer(CO),namely(MoECO),to jointly optimize the computation offloading and task scheduling in cloud-fog networks to minimize two competing objectives,i.e.,energy consumption and communication delay.MoECO first assigns tasks to the optimal computational nodes and then the allocated tasks are scheduled for processing based on the task priority.The mathematical modelling of CO needs improvement in computation time and convergence speed.Therefore,MoECO is proposed to increase the search capability of agents by controlling the search strategy based on a leader’s location.The adaptive step length operator is adjusted to diversify the solution and thus improves the exploration phase,i.e.,global search strategy.Consequently,this prevents the algorithm from getting trapped in the local optimal solution.Moreover,the interaction factor during the exploitation phase is also adjusted based on the location of the prey instead of the adjacent Cheetah.This increases the exploitation capability of agents,i.e.,local search capability.Furthermore,MoECO employs a multi-objective Pareto-optimal front to simultaneously minimize designated objectives.Comprehensive simulations in MATLAB demonstrate that the proposed algorithm obtains multiple solutions via a Pareto-optimal front and achieves an efficient trade-off between optimization objectives compared to baseline methods. 展开更多
关键词 Computation offloading task scheduling cheetah optimizer fog computing optimization resource allocation internet of things
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Energy Aware Task Scheduling of IoT Application Using a Hybrid Metaheuristic Algorithm in Cloud Computing 认领 引用
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作者 Ahmed Awad Mohamed Eslam Abdelhakim Seyam +4 位作者 Ahmed R.Elsaeed Laith Abualigah Aseel Smerat Ahmed M.AbdelMouty Hosam E.Refaat 《Computers, Materials & Continua》 SCIE EI 2026年第3期1786-1803,共18页
In recent years,fog computing has become an important environment for dealing with the Internet of Things.Fog computing was developed to handle large-scale big data by scheduling tasks via cloud computing.Task schedul... In recent years,fog computing has become an important environment for dealing with the Internet of Things.Fog computing was developed to handle large-scale big data by scheduling tasks via cloud computing.Task scheduling is crucial for efficiently handling IoT user requests,thereby improving system performance,cost,and energy consumption across nodes in cloud computing.With the large amount of data and user requests,achieving the optimal solution to the task scheduling problem is challenging,particularly in terms of cost and energy efficiency.In this paper,we develop novel strategies to save energy consumption across nodes in fog computing when users execute tasks through the least-cost paths.Task scheduling is developed using modified artificial ecosystem optimization(AEO),combined with negative swarm operators,Salp Swarm Algorithm(SSA),in order to competitively optimize their capabilities during the exploitation phase of the optimal search process.In addition,the proposed strategy,Enhancement Artificial Ecosystem Optimization Salp Swarm Algorithm(EAEOSSA),attempts to find the most suitable solution.The optimization that combines cost and energy for multi-objective task scheduling optimization problems.The backpack problem is also added to improve both cost and energy in the iFogSim implementation as well.A comparison was made between the proposed strategy and other strategies in terms of time,cost,energy,and productivity.Experimental results showed that the proposed strategy improved energy consumption,cost,and time over other algorithms.Simulation results demonstrate that the proposed algorithm increases the average cost,average energy consumption,and mean service time in most scenarios,with average reductions of up to 21.15%in cost and 25.8%in energy consumption. 展开更多
关键词 Energy-efficient tasks internet of things(IoT) cloud fog computing artificial ecosystem-based optimization salp swarm algorithm cloud computing
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Neuromorphic Computing of Multimodal Temporal Data for Machine Fault Diagnosis:Methodology and Hardware Deployment 认领 引用
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作者 Weipeng Fan Xiang Li +3 位作者 Yaguo Lei Shupeng Yu Naipeng Li Bin Yang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第6期1515-1517,共3页
Dear Editor,Long-term monitoring of different mechanical signals is vital for the health management of modern industrial equipment.Traditional deep learning-based fault diagnosis methods rely much on high-performance ... Dear Editor,Long-term monitoring of different mechanical signals is vital for the health management of modern industrial equipment.Traditional deep learning-based fault diagnosis methods rely much on high-performance computing systems and are difficult to be always-on deployed at the edge.Meanwhile,most of the existing fault diagnosis methods rely on single-sourced sensing data,which only capture limited fault information and cannot well reflect the machine health condition.To address the aforementioned problems,the bio-inspired spiking neural networks(SNNs)offer a promising solution,which simulates the structure and operation of biological neural systems and is more energy and computation-efficient. 展开更多
关键词 computation efficiency fault diagnosis energy efficiency mechanical signals bio inspired spiking neural networks health management multimodal temporal data machine fault diagnosis
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From portfolio optimization to quantum blockchain and security: a systematic review of quantum computing in finance 认领 引用
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作者 Abha Satyavan Naik Esra Yeniaras +2 位作者 Gerhard Hellstern Grishma Prasad Sanjay Kumar Lalta Prasad Vishwakarma 《Financial Innovation》 2025年第1期2536-2602,共67页
The rapid advancement of quantum computing has sparked a considerable increase in research attention to quantum technologies.These advances span fundamental theoretical inquiries into quantum information and the explo... The rapid advancement of quantum computing has sparked a considerable increase in research attention to quantum technologies.These advances span fundamental theoretical inquiries into quantum information and the exploration of diverse applications arising from this evolving quantum computing paradigm.The scope of the related research is notably diverse.This paper consolidates and presents quantum computing research related to the financial sector.The finance applications considered in this study include portfolio optimization,fraud detection,and Monte Carlo methods for derivative pricing and risk calculation.In addition,we provide a comprehensive analysis of quantum computing’s applications and effects on blockchain technologies,particularly in relation to cryptocurrencies,which are central to financial technology research.As discussed in this study,quantum computing applications in finance are based on fundamental quantum physics principles and key quantum algorithms.This review aims to bridge the research gap between quantum computing and finance.We adopt a two-fold methodology,involving an analysis of quantum algorithms,followed by a discussion of their applications in specific financial contexts.Our study is based on an extensive review of online academic databases,search tools,online journal repositories,and whitepapers from 1952 to 2023,including CiteSeerX,DBLP,Research-Gate,Semantic Scholar,and scientific conference publications.We present state-of-theart findings at the intersection of finance and quantum technology and highlight open research questions that will be valuable for industry practitioners and academicians as they shape future research agendas. 展开更多
关键词 Portfolio optimization Fraud detection Derivative pricing Risk calculation Monte carlo Quantum blockchain Quantum-resistant blockchain Digital signature algorithms Post-quantum cryptography Security Privacy-preserving blockchain Quantum computing
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Quantum computing-enhanced topology optimization with stress constraints for truss structures 认领 引用 被引量：2
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作者 Yan Wang Dixiong Yang +1 位作者 Zhenzeng Lei Guohai Chen 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第6期41-57,共17页
Quantum computing,leveraging the properties of quantum physics such as quantum superposition and entanglement,possesses the potential for exponential acceleration compared to classical computing.It can significantly e... Quantum computing,leveraging the properties of quantum physics such as quantum superposition and entanglement,possesses the potential for exponential acceleration compared to classical computing.It can significantly enhance solution efficiency in topology optimization and effectively avoid the entrapment in local optima.This paper proposes a hybrid classical-quantum computing framework to solve the stress-constrained topology optimization problem for truss structures.Initially,structural analyses are performed on a classical computer to determine the stresses of truss members.Then,the optimization problem is formulated through incremental updates of member cross-sectional areas to make it compatible with a quantum annealer.The update strategy consists of a directional-control function and a magnitude-control function.By embedding stress constraints directly into the directional-control function,the original optimization problem is reformulated as a quadratic unconstrained binary optimization model suitable for quantum annealing.To realize a balance between solution accuracy and iteration efficiency,a dynamic strategy for adjusting the magnitude of area increments is proposed.Thus,the quantum annealer can effectively achieve the optimal solutions.When only the access time of the quantum processing unit is considered,the results from 2D and 3D examples of truss topology optimization validate the effectiveness of the proposed framework,and demonstrate the great potential of quantum computing in structural optimization. 展开更多
关键词 Topology optimization Truss structures Quantum computing Quantum annealing algorithm Quadratic unconstrained binary optimization problem
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Correction:In-Sensor-Memory Computing for Post-Von Neumann Intelligence:A Perspective 认领 引用
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作者 Hongyu Tang Ninghai Yu +2 位作者 Pengsheng Min Ruiqian Guo Guoqi Zhang 《Nano-Micro Letters》 SCIE EI CAS CSCD 2026年第10期844-844,共1页
Correction to:Nano-Micro Lett.(2026)18:338 http://gffzzd3cc09b8251d45dfsuo5bp9qfxuwv6v55.ffgz.tsg.suse.edu.cn/10.1007/s40820-026-02191-y e-ISSN 2150-5551 CN 31-2103/TB CORRECTION Cite as Nano-Micro Lett.(2026)18:369©The Author(s)2026 http://gffzzd3cc09b8251d45dfsuo5bp9qfxuwv6v55.ffgz.tsg.suse.edu.cn/10.1007/s4082... Correction to:Nano-Micro Lett.(2026)18:338 http://gffzzd3cc09b8251d45dfsuo5bp9qfxuwv6v55.ffgz.tsg.suse.edu.cn/10.1007/s40820-026-02191-y e-ISSN 2150-5551 CN 31-2103/TB CORRECTION Cite as Nano-Micro Lett.(2026)18:369©The Author(s)2026 http://gffzzd3cc09b8251d45dfsuo5bp9qfxuwv6v55.ffgz.tsg.suse.edu.cn/10.1007/s40820-026-02217-5 The original article can be found online at http://gffzzd3cc09b8251d45dfsuo5bp9qfxuwv6v55.ffgz.tsg.suse.edu.cn/10.1007/s40820-026-02191-y.*Hongyu Tang,hongyu_tang@fudan.edu.cn;Ruiqian Guo,rqguo@fudan.edu.cn 1 College of Intelligent Robotics and Advanced Manufacturing,Fudan University,Shanghai 200433,People’s Republic of China 2 Shanghai Engineering Technology Research Center for SiC Power Device,Fudan University,Shanghai 200433,People’s Republic of China 3 EEMCS Faculty,Delft University of Technology,Delft 2628CD,The Netherlands Following publication of the original article[1],the authors reported that the Acknowledgments and Authors’Contributions sections need to be updated.The incorrect version is:Acknowledgements Ruiqian Guo contributed to concep-tualization,review,and supervision.Guoqi Zhang contrib-uted to review and feedback.Author Contributions Hongyu Tang contributed to investigation,original draft writing,visualization,and funding acquisition.Ninghai Yu and Pengsheng Min were involved in original draft writing,visualization,and review.Ruiqian Guo and Guoqi Zhang contributed to conceptualiza-tion,review,and supervision. 展开更多
关键词 sensor memory computing advanced manufacturingfudan authors contributions post von neumann intelligence acknowledgments intelligent robotics nano micro lett
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Optical Chips for Quantum Computing and Networking 认领 引用
19
《Bulletin of the Chinese Academy of Sciences》 2026年第2期125-127,共3页
The 2026 Tan Kah Kee Young Scientist Award in Information Technical Sciences recognizes the breakthrough work on integrated optical quantum chips led by Professor WANG Jianwei and Professor GONG Qihuang at Peking Univ... The 2026 Tan Kah Kee Young Scientist Award in Information Technical Sciences recognizes the breakthrough work on integrated optical quantum chips led by Professor WANG Jianwei and Professor GONG Qihuang at Peking University.Their team has built chips that combine quantum light sources,optical circuits,and light detectors all on a millimeter-scale chip.This makes it possible to generate,control,and measure quantum states entirely on a single chip,providing a hardware platform that can be scaled up for quantum computing and networking. 展开更多
关键词 light detectors networking integrated optical quantum chips quantum light sourcesoptical circuitsand professor wang jianwei hardware platform quantum computing optical chips
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Computing over Space:Status,Challenges,and Opportunities 认领 引用 被引量：9
20
作者 Yaoqi Liu Yinhe Han +3 位作者 Hongxin Li Shuhao Gu Jibing Qiu Ting Li 《Engineering》 SCIE EI CSCD 2025年第11期20-25,共6页
1.Introduction The rapid expansion of satellite constellations in recent years has resulted in the generation of massive amounts of data.This surge in data,coupled with diverse application scenarios,underscores the es... 1.Introduction The rapid expansion of satellite constellations in recent years has resulted in the generation of massive amounts of data.This surge in data,coupled with diverse application scenarios,underscores the escalating demand for high-performance computing over space.Computing over space entails the deployment of computational resources on platforms such as satellites to process large-scale data under constraints such as high radiation exposure,restricted power consumption,and minimized weight. 展开更多
关键词 satellite constellations deployment computational resources data processing space computing radiation exposure space high performance computing power consumption
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