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Proceedings of the 55th Annual IEEE/ACM International Symposium on Microarchitecture

作者： Jawad Haj Yahya Haris Volos Davide B. Bartolini Georgia Antoniou Jeremie S. Kim Zhe Wang Kleovoulos Kalaitzidis Tom Rollet Zhirui Chen Ye Geng Onur Mutlu Yiannakis Sazeides Rivos Inc Mountain View California United States Computer Architecture Laboratory Department of Computer Science University of Cyprus Computing Systems Lab Huawei Zurich Research Center Department of Information Technology and Electrical Engineering ETH Zurich Switzerland

ISBN: (纸本)9781665462723

User-facing applications running in modern datacenters exhibit irregular request patterns and are implemented using a multitude of services with tight latency requirements (30--250μs). These characteristics render existing energy-conserving techniques ineffective when processors are idle due to the long transition time (order of 100μs) from a deep CPU core idle power state (C-state). While prior works propose management techniques to mitigate this inefficiency, we tackle it at its root with AgileWatts (AW): a new deep CPU core C-state architecture optimized for datacenter server processors targeting latency-sensitive *** drastically reduces the transition latency from deep CPU core idle power states while retaining most of their power savings based on three key ideas. First, AW eliminates the latency (several microseconds) of saving/restoring the core context when powering-off/-on the core in a deep idle state by i) implementing medium-grained power-gates, carefully distributed across the CPU core, and ii) retaining context in the power-ungated domain. Second, AW eliminates the flush latency (several tens of microseconds) of the L1/L2 caches when entering a deep idle state by keeping L1/L2 content power-ungated. A small control logic also remains ungated to serve cache coherence traffic. AW implements cache sleep-mode and leakage reduction for the power-ungated domain by lowering a core's voltage to the minimum operational level. Third, using a state-of-the-art power efficient all-digital phase-locked loop (ADPLL) clock generator, AW keeps the PLL active and locked during the idle state, cutting microseconds of wake-up latency at negligible power *** evaluation with an accurate industrial-grade simulator calibrated against an Intel Skylake server shows that AW reduces the energy consumption of Memcached by up to 71% (35% on average) with <1% end-to-end performance degradation. We observe similar trends for other evaluated services (MySQL and Kafka).

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HeteroSys: Heterogeneous and Collaborative Sensing in the Wild

HeteroSys: Heterogeneous and Collaborative Sensing in the Wi...

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International Conference on smart Computing (smartCOMP)

作者： Indrajeet Ghosh Adam Goldstein Avijoy Chakma Jade Freeman Timothy Gregory Niranjan Suri Sreenivasan Ramasamy Ramamurthy Nirmalya Roy Department of Information Systems University of Maryland Baltimore County United States Department of Electrical Engineering and Computer Science UC Berkeley United States DEVCOM Army Research Lab Department of Computer Science Bowie State University United States

Advances in Internet-of-Things, artificial intelligence, and ubiquitous computing technologies have contributed to building the next generation of context-aware heterogeneous systems with robust interoperability to control and monitor the environmental variables of smart environments. Motivated by this, we propose HeteroSys, an end-to-end multi-functional smart IoT-based system prototype for heterogeneous and collaborative sensing in a smart IoT-based environment. A unique characteristic of HeteroSys is that it relies on Home Assistant (HA) to collate heterogeneous sensors (e.g., passive infrared sensors (PIR), reed (door) switches, object tags, wearable wrist-mounted, water leak sensors, and internet protocol cameras), and uses a variety of networking protocols such as Zigbee open standard for mesh networking, WiFi, and Bluetooth Low Energy (BLE) for communication. The reliance on HA (and its broad community support) makes HeteroSys ideal for various applications such as object detection, human activity recognition and behavior patterns. We articulated the development phase, integration, testing challenges and evaluation of the HeteroSys. We conducted an extensive 24-hour longitudinal data collection from 5 participants performing 6 activities by deploying in an indoor home environment. Our assessment of the acquired dataset reveals that the representations learned using deep learning architecture aid in improving the detection of activities to 83.1% accuracy.

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Optimal Resource Utilization in Hyperledger Fabric: A Comprehensive SPN-Based Performance Evaluation Paradigm

Optimal Resource Utilization in Hyperledger Fabric: A Compre...

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IEEE Symposium on Network Operations and Management

作者： Carlos Melo Glauber Gonçalves Francisco A. Silva Leonel Feitosa Iure Fé André Soares Eunmi Choi Tuan Anh Nguyen Dugki Min Applied Research on Distributed Systems Lab (PASID) Federal University of Piauí (UFPI) Brazil School of Software College of Computer Science Kookmin University Seoul South Korea Konkuk Aerospace Design-Airworlhiness Research Inslilule (KADA) Konkuk Universily Seoul Soulh Korea Department of Computer Science and Engineering Konkuk University Seoul South Korea

ISBN: (数字)9798350327939

ISBN: (纸本)9798350327946

Hyperledger Fabric stands as a leading framework for permissioned block-chain systems, ensuring data security and audit-ability for enterprise applications. As applications on this platform grow, understanding its complex configuration concerning various block-chain parameters becomes vital. These configurations significantly affect the system’s performance and cost. In this research, we introduce a Stochastic Petri Net (SPN) model to analyze Hyper-ledger Fabric’s performance, considering variations in block-chain parameters, computational resources, and transaction rates. We provide case studies to validate the utility of our model, aiding block-chain administrators in determining optimal configurations for their applications. A key observation from our model highlights the block size’s role in system response time. We noted an increased mean response time, between 1 to 25 seconds, due to variations in transaction arrival rates.

关键词： Performance evaluation Distributed ledger Computational modeling Data security Petri nets Stochastic processes Fabrics

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Physics-Based Approach to Efficient Electromagnetic Modeling of Multiscale Antennas with Metasurfaces 34

Physics-Based Approach to Efficient Electromagnetic Modeling...

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34th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2021

作者： Mittra, Raj Nasri, Abdelkhalek Ghalib, Asim University of Central Florida EMC Lab Electrical and Computer Engineering Department OrlandoFL32816 United States Research Laboratory Smart Electricity and ICT SEICT LR18ES44. National Engineering School of Carthage University of Carthage Tunisia

ISBN: (纸本)9789463968027

This paper presents a novel 'physics-based' technique for numerically modeling of multi-scale problems, e.g., antennas with metasurfaces operating at mm wavelengths. The metasurface is replaced by an Equivalent Dielectric (ED) medium, whose use in the numerical simulation significantly reduces the computational resources required to model the problem. Furthermore, the proposed method is accurate and does not need sophisticated new code development but can be used in the existing commercially available software instead. © 2021 URSI.

关键词： Antennas

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Gradient-Guided Modality Decoupling for Missing-Modality Robustness

arXiv

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arXiv 2024年

作者： Wang, Hao Luo, Shengda Hu, Guosheng Zhang, Jianguo Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Oosto BelfastBT1 2BE United Kingdom Peng Cheng Lab Shenzhen China

Multimodal learning with incomplete input data (missing modality) is practical and challenging. In this work, we conduct an in-depth analysis of this challenge and find that modality dominance has a significant negative impact on the model training, greatly degrading the missing modality performance. Motivated by Grad-CAM, we introduce a novel indicator, gradients, to monitor and reduce modality dominance which widely exists in the missing-modality scenario. In aid of this indicator, we present a novel Gradient-guided Modality Decoupling (GMD) method to decouple the dependency on dominating modalities. Specifically, GMD removes the conflicted gradient components from different modalities to achieve this decoupling, significantly improving the performance. In addition, to flexibly handle modal-incomplete data, we design a parameter-efficient Dynamic Sharing (DS) framework which can adaptively switch on/off the network parameters based on whether one modality is available. We conduct extensive experiments on three popular multimodal benchmarks, including BraTS 2018 for medical segmentation, CMU-MOSI, and CMU-MOSEI for sentiment analysis. The results show that our method can significantly outperform the competitors, showing the effectiveness of the proposed solutions. Our code is released here: https://***/HaoWang420/Gradientguided-Modality-Decoupling. Copyright © 2024, The Authors. All rights reserved.

关键词： Sentiment analysis

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A Comprehensive Review of Active EV Battery Cell Voltage Balancing systems: Current Issues and Prospective Solutions

A Comprehensive Review of Active EV Battery Cell Voltage Bal...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Chandan Chetri Alvin Huynh Sheldon S. Williamson Department of Electrical Computer and Software Engineering Smart Transportation Electrification and Energy Research (STEER) Group Advanced Storage Systems and Electric Transportation (ASSET) Laboratory Faculty of Engineering and Applied Science Ontario Tech University Oshawa Canada

The performance of a battery pack is greatly affected by an imbalance between the cells. Cell balancing is a very important criterion for Battery Management System (BMS) to operate properly. This paper presents the various cell balancing topologies which have been presented by various researchers in the past years. A novel topology has also been discussed, which improves the overall efficiency of the components being used. Various comparison parameters such as Control, Speed, Efficiency, Power Effects, Manufacturability, Size, and Cost have been considered.

关键词： Industrial electronics Electric potential Costs Equalizers Battery management systems Transformers Power electronics

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Cellulose-Based Nanocomposite Insulation Material with Excellent Thermal Aging Resistance: KH550-hBN-Modified Cellulose Insulation Paper

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IEEE Transactions on Dielectrics and Electrical Insulation 2025年

作者： Wang, Zuhao Peng, Xiao Chronis, Ioannis Wu, Yingrui Psomopoulos, Constantinos S. Tang, Chao Southwest University College of Engineering and Technology International R & D Center for New Technologies of Smart Grid and Equipment Chongqing400715 China Southwest University College of Engineering and Technology Chongqing400715 China Chongqing University State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing400044 China University of West Attica High Voltage and Energy Systems Research Lab Dept. of Electrical and Electronics Engineering EgaleoGR-122 44 Greece

As the global power industry evolves, transformer insulation systems face increasing challenges. The aging of cellulose insulation paper (cellulose-IP) at elevated temperatures significantly impacts its insulation properties and overall lifespan. To enhance the thermal aging resistance and industrial usability of cellulose-IP, this study employs nano-boron nitride (h-BN) along with three silane coupling agents - 3-ammonopropyltriethoxysilane (KH550), 3-glycidyloxypropyltrimethoxysilane (KH560), and 3-methacryloyloxypropyltrimethoxysilane (KH570) - to modified cellulose-IP. Upon evaluating the properties and simulation results of the modified cellulose-IP, KH550-hBN demonstrated superior properties and was selected for an accelerated thermal aging test lasting 60 days. The results indicated that KH550-hBN effectively mitigates the degradation of cellulose-IP. In the late aging stage, the mechanical properties of the modified cellulose-IP deteriorated more slowly than those of pure cellulose-IP. Additionally, thermal conductivity improved by 26.9%, while breakdown field strength increased by 12.1%. The introduction of KH550-hBN promotes the formation of a complete thermal conductivity network within the cellulose matrix, increases the number of intermolecular hydrogen bonds and introduces nano-barrier regions. These improvements enhance the interactions between the cellulose systems and effectively inhibit the generation and migration of polar derivatives during the aging process, resulting in a significant improvement in the longevity and stability of transformer internal insulation systems. © 1994-2012 IEEE.

关键词： Boron nitride

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GUEST EDITORIAL

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China Communications 2023年第2期 3-6页

作者： Yuan Wu Xu Chen Feng Lyu Xianfu Chen Xumin Huang Jie Gao Yueyue Dai Tony Q.S.Quek Yan Zhang the State Key Laboratory of Internet of Things for Smart City University of Macau the Department of Computer and Information Science University of Macau Sun Yat-sen University Sun Yat-sen University Institute of Advanced Networking and Computing Systems Sun Yat-sen University National and Local Joint Engineering Laboratory the School of Computer Science and Engineering Central South University the VTT Technical Research Centre of Finland the School of Automation Guangdong University of Technology the School of Information Technology Carleton University Huazhong University of Science and Technology Singapore University of Technology and Design(SUTD) the IEEE Communications Society Technical Committee on Green Communications and Computing(TCGCC)

With the growing maturity of the advanced edge-cloud collaboration and integrated sensing-communication-computing systems, edge intelligence has been envisioned as one of the enabling technologies for ubiquitous and l...

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PAKE – PoS Tagger Augmented Keyword Extraction

PAKE – PoS Tagger Augmented Keyword Extraction

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Computing, Applications and systems (COMPAS), IEEE International Conference on

作者： Md Saidur Rahman Kohinoor Ayesha Loylus Miah Shah Fayez Ali Md Sabir Hossain Md. Hasan Imam Bijoy Shadman Sakib Information and Computer Science King Fahd U. of Petroleum & Minerals Dhahran Saudi Arabia AI & NLP Discipline InteX Research Lab Sylhet Bangladesh Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Information Systems University of Maryland Baltimore County United States

ISBN: (数字)9798331529765

ISBN: (纸本)9798331529772

The state-of-the-art techniques for automatic keyword extraction majorly deal with the collection of long documents. However, for several reasons, these do not provide satisfactory results for shorter lengths of documents. Moreover, with the ever-increasing amounts of information available, a keyword extraction system that automatically deals with varying lengths of text can lessen the workload and make the entire process of manually assigning the keywords less time-consuming. For this, the widely used Natural Language Processing (NLP) techniques are examined in the context of extensive data. Therefore, this research introduces PAKE - PoStagger Augmented Keyword Extraction system as a practical amalgamation of statistical and textual-based features based on an unsupervised key phrase extracting algorithm to stand out as a suitable alternative to the existing solutions. The effectiveness is demonstrated by comparing it with six state-of-the-art unsupervised methods, and the results are illustrated using four datasets.

关键词： Semantics Tagging Feature extraction Natural language processing Data mining

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Disambiguation of Chinese Polyphones in an End-to-End Framework with Semantic Features Extracted by Pre-trained BERT

arXiv

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arXiv 2025年

作者： Dai, Dongyang Wu, Zhiyong Kang, Shiyin Wu, Xixin Jia, Jia Su, Dan Yu, Dong Meng, Helen Tsinghua-CUHK Joint Research Center for Media Sciences Technologies and Systems Graduate School at Shenzhen Tsinghua University Shenzhen China Department of Computer Science and Technology Tsinghua University Beijing China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Shatin N.T. Hong Kong Tencent AI Lab. Tencent Shenzhen China

Grapheme-to-phoneme (G2P) conversion serves as an essential component in Chinese Mandarin text-to-speech (TTS) system, where polyphone disambiguation is the core issue. In this paper, we propose an end-to-end framework to predict the pronunciation of a polyphonic character, which accepts sentence containing polyphonic character as input in the form of Chinese character sequence without the necessity of any preprocessing. The proposed method consists of a pre-trained bidirectional encoder representations from Transformers (BERT) model and a neural network (NN) based classifier. The pre-trained BERT model extracts semantic features from a raw Chinese character sequence and the NN based classifier predicts the polyphonic character’s pronunciation according to BERT output. In out experiments, we implemented three classifiers, a fully-connected network based classifier, a long short-term memory (LSTM) network based classifier and a Transformer block based classifier. The experimental results compared with the baseline approach based on LSTM demonstrate that, the pre-trained model extracts effective semantic features, which greatly enhances the performance of polyphone disambiguation. In addition, we also explored the impact of contextual information on polyphone disambiguation. Copyright © 2025, The Authors. All rights reserved.

关键词： Semantics

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