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RAJA Performance Suite: Performance Portability Analysis with Caliper and Thicket 24

RAJA Performance Suite: Performance Portability Analysis wit...

Proceedings of the SC '24 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis

作者： Olga Pearce Jason Burmark Rich Hornung Befikir Bogale Ian Lumsden Michael McKinsey Dewi Yokelson David Boehme Stephanie Brink Michela Taufer Tom Scogland Lawrence Livermore National Laboratory Livermore CA USA and Department of Computer Science and Engineering Texas A&M University College Station TX USA Lawrence Livermore National Laboratory Livermore CA USA Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA Department of Computer Science and Engineering Texas A&M University College Station TX USA

ISBN: (纸本)9798350355543

Maintaining performant code in a world of fast-evolving computer architectures and programming models poses a significant challenge to scientists. Typically, benchmark codes are used to model some aspects of a large application code's performance, and are easier to build and run. Such benchmarks can help assess the effects of code or algorithm changes, system updates, and new hardware. However, most performance benchmarks are not written using a wide range of GPU programming models. The RAJA Performance Suite provides a comprehensive set of computational kernels implemented in a variety of programming models. We integrated the performance measurement and analysis tools Caliper and Thicket into the RAJA Performance Suite to facilitate performance comparison across kernel implementations and architectures. This paper describes the RAJA Performance Suite, performance metrics that can be collected, and experimental analysis with case studies. The RAJA Performance Suite and integration of Caliper and Thicket enabled us to effectively measure the variety of implementations on the variety of hardware, and automatically characterize subsets of kernels which exhibit similar bottlenecks---and therefore perform similarly on new architectures which provide a different balance between resources such as FLOPS and memory bandwidth. We definitively demonstrate that the most memory bound kernels show the most performance gains on architectures with high-bandwidth memory (HBM), and that the kernels that have other bottleneck may, to a lesser extent, benefit from the higher-FLOPS GPUs.

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Time Series Prediction of Power System Events Using LSTM, GRU, and Transformer Networks to Increase Computation Efficiency

Time Series Prediction of Power System Events Using LSTM, GR...

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IEEE General Meeting Power& Energy Society

作者： Naga Lakshmi Thotakura Zhihao Jiang Yilu Liu Department of Electrical and Computer Engineering The University of Tennessee Knoxville TN USA Oak Ridge National Laboratory Oak Ridge TN USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

The growing complexity of interconnected power systems increases dynamic simulation time, creating computational challenges. To improve efficiency, researchers explore model reduction strategies, focusing on a study area while approximating external regions. Measurement-based techniques to represent these areas through dynamic loads. Recurrent Neural Networks (RNNs), such as long short-term memory (LSTM), gated recurrent unit (GRU), and Transformers, excel at predicting non-linear power system behavior. In this study, we apply RNN models to the Northeast Power Coordinating Council (NPCC) 140-bus system, with two equivalent loads representing external areas. We forecast time-series power system events, including generator and load trips. The results confirm the RNN models' accuracy in predicting power system behavior during events, showcasing their potential for event prediction.

关键词： Recurrent neural networks Computational modeling Power system dynamics Time series analysis Predictive models Transformers Transmission line measurements Reduced order systems Long short term memory Load modeling

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An Architecture for Virtual Tethering of ROVs

An Architecture for Virtual Tethering of ROVs

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OCEANS

作者： Rajat Mishra Mandar Chitre Bharath Kalyan Yuen Min Too Hari Vishnu Luyuan Peng Acoustic Research Laboratory Tropical Marine Science Institute National University of Singapore Department of Electrical & Computer Engineering National University of Singapore

ISBN: (数字)9798350362077

ISBN: (纸本)9798350362084

We introduce an architecture designed for wireless Remote Operated Vehicle (ROV) operations during intervention surveys. Using the recent advancements in 3D modeling, visual odometry, video compression, and underwater communication, our approach aims to facilitate fully wireless ROV operations. The proposed architecture comprises several modular blocks, each with versatile applications spanning diverse domains, including multiplayer gaming, remote rover control and video transmission over a low-bandwidth connection. This comprehensive framework signifies progress in ROV operations, replacing the traditional physical tether with a software-defined virtual tether.

关键词： Wireless communication Surveys Underwater communication Three-dimensional displays Oceans computer architecture Video compression

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Towards Continuous Development for Quantum Programming in Decentralized IoT environments

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Procedia computer Science 2024年 238卷 7-14页

作者： Michail Alexandros Kourtis Nikolay Tcholtchev Ilie-Daniel Gheorghe-Pop Colin Kai-Uwe Becker Georgios Xylouris Evangelos Markakis Matic Petric Raphael Seidel Sebastian Bock National Center of Scientific Research “Demokritos” Athens Greece Fraunhofer Institute for Open Communication Systems (FOKUS) Berlin Germany Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Greece

The progression in quantum computing and the rapid development of quantum computation hardware has raised expectations for its application to commercially relevant use cases in the future. However, the need for high-level quantum programming abstractions and targeted use cases paired with vertical applications, which can directly benefit from quantum computing, remains an open challenge. This paper presents our vision for a decentralized architecture for swarm based IoT systems that leverages a high-level continuous development and integration quantum programming suite to support edge processing capabilities for different use cases across the edge-fog-cloud continuum. The planned Quantum DevKit provides the necessary abstractions and low-level backend interfaces for quantum computing infrastructure, enabling edge computation using quantum processing, with extensions to efficient management of Service Level Agreements (SLAs). The paper focuses on the presentation of the development kit and its coupling swarm-based architecture that automates the orchestration of the cloud-to-edge continuum, showcasing the potential of quantum technology in edge processing.

关键词： Quantum Programming Swarm Intelligence Decentralized Computing Edge Blockchain

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Differential Evolution for Optimizing Parameter Estimation in Practical D2D Channels

Differential Evolution for Optimizing Parameter Estimation i...

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IEEE Conference on Wireless Communications and Networking

作者： Samuel B. Ferreira Gomes Nidhi Simmons Michel Daoud Yacoub Paschalis C. Sofotasios Simon L. Cotton Wireless Technology Laboratory School of Electrical and Computer Engineering University of Campinas Campinas Brazil Centre for Wireless Innovation School of Electronics Electrical Engineering and Computer Science Queen's University Belfast Belfast UK Department of Computer and Communication Engineering C2PS and 6G Center Khalifa University Abu Dhabi UAE Department of Electrical Engineering Tampere University Tampere Finland

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Inspired by the theory of natural evolution, Differential Evolution (DE) functions constitute an optimization tool in the field of evolutionary algorithms. Here, we propose employing DE to estimate physically acceptable fading parameters in device-to-device (D2D) communication channels. We examine four real-world D2D propagation channel measurements obtained under various conditions: indoor, outdoor, line-of-sight (LOS), and non-LOS. Four popular fading models, $\kappa-\mu, \eta-\mu, \kappa-\mu$ /inverse gamma, and $\eta-\mu$ /inverse gamma are used to characterize these links. Two fitness functions, Kullback-Leibler divergence (KLD) and mean squared error (MSE), are utilized for evaluation. We also compare the DE with another evolutionary algorithm, namely the genetic algorithm (GA). Notably, our results demonstrate that while both algorithms deliver excellent estimation performances, DE emerges as significantly faster and more robust compared to GA. Regarding fitness performances, the algorithm, when paired with KLD, outperforms the pairing with MSE, as assessed through the minimization of the Akaike information criterion.

关键词： Fading channels Parameter estimation Metaheuristics Estimation Channel estimation Line-of-sight propagation Evolutionary computation

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Soft computing-based predictive modeling of flexible electrohydrodynamic pumps

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Biomimetic Intelligence & Robotics 2023年第3期3卷 30-37页

作者： Zebing Mao Yanhong Peng Chenlong Hu Ruqi Ding Yuhei Yamada Shingo Maeda Department of Mechanical Engineering Tokyo Institute of TechnologyTokyo 152-8550Japan Department of Information and Communication Engineering Graduate School of EngineeringNagoya UniversityNagoya 464-8603Japan Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Key Laboratory of Conveyance and Equipment Ministry of EducationEast China Jiaotong UniversityNanchang 330013China Living Systems Materialogy(LiSM)Research Group International Research Frontiers Initiative(IRFI)Tokyo Institute of TechnologyYokohama 226-8501Japan

Flexible electrohydrodynamic(EHD)pumps have been developed and applied in many fields due to no transmission structure,no wear,easy manipulation,and no *** simulation is often used to predict the output performance of flexible EHD ***,this method neglects fluid–solid interaction and energy loss caused by flexible materials,which are both difficult to calculate when the flexible pumps ***,this study proposes a flexible pump output performance prediction using machine learning *** used three different types of machine learning:random forest regression,ridge regression,and neural network to predict the critical parameters(pressure,flow rate,and power)of the flexible EHD ***,angle,gap,overlap,and channel height are selected as five input data of the neural *** addition,we optimized essential parameters in the three ***,we adopt the best predictive model and evaluate the significance of five input parameters to the output performance of the flexible EHD *** the three methods,the MLP model has exceptionally high accuracy in predicting pressure and *** work is beneficial for the design process of fluid sources in flexible soft actuators and soft hydraulic sources in microfluidic chips.

关键词： Electrohydrodynamic pumps Neural network Rigid regression Random forest regression

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InfaSafe: A Comprehensive, Non-invasive Infant Monitoring System

InfaSafe: A Comprehensive, Non-invasive Infant Monitoring Sy...

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IEEE International Conference on Electro-Information Technology

作者： Lukas Klicker Alex Maliwat Joanna Findura Xinrui Yu Mikhail Gromov Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing (ECASP) Research Laboratory Illinois Institute of Technology Chicago IL USA

ISBN: (数字)9798350330649

ISBN: (纸本)9798350330656

InfaSafe emerges as a novel approach to infant health monitoring, uniquely positioned at the convergence of advanced artificial intelligence and edge computing. This system is designed not as a definitive solution but as an advanced platform for comprehensive data archiving, offering valuable insights into the complex and elusive nature of Sudden Unexpected Infant Death (SUID). InfaSafe utilizes AI algorithms for real-time pose estimation, breathing surveillance, and cry analysis, all within an edge computing framework that facilitates prompt and efficient data handling. This paper explores the development and capabilities of InfaSafe, underscoring its role in providing crucial, real-time insights and alerts for caregivers and its potential to contribute significantly to our understanding of neonatal health and SUID. The focus is on leveraging technological advancements to gather comprehensive data, which can be instrumental in shaping future research and interventions in neonatal care.

关键词： Temperature sensors Temperature measurement Pediatrics Temperature distribution Prototypes Real-time systems Thermal analysis

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Voltage Profile Improvement in Unbalanced Distribution Networks for Probabilistic Generation and Consumption

Voltage Profile Improvement in Unbalanced Distribution Netwo...

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International Conference on Probabilistic Methods Applied to Power systems (PMAPS)

作者： Mohammed Bamatraf Oğuzhan Ceylan Ioana Pisica Aydoğan Özdemir Department of Electrical Eng. Istanbul Technical University Turkey Department of Management Information Systems Kadir Has University Turkey Department of Electrical and Computer Engineering Brunel University London UK Department of Electrical and Electronics Engineering Kadir Has University Turkey

ISBN: (数字)9798350372786

ISBN: (纸本)9798350372793

Due to their technical, economical, and environmental advantages, active distribution networks implement renewable energy resources (RERs) such as photovoltaic (PV) units in distribution networks DNs. However, some drawbacks may arise due to the intermittent nature of RERs, such as voltage fluctuations and increased system losses. This paper presents an optimization problem that is solved by sequential linear programming (SLP) to improve the voltage profile of the unbalanced distribution network. A probabilistic approach was applied to both the load profile and the active power generation of the PV units. SLP is applied to the modified IEEE 34 Bus Test system. The method optimizes the voltage deviations by changing the taps of the voltage regulators and the reactive power injected by the inverters of the PV systems and, in some cases, by switching a shunt capacitor. MATLAB simulations are done at different times of the day with different loads and PV outputs to compare base case and optimal case voltage profiles. The results show better voltage profiles after applying the presented approach.

关键词： Reactive power Regulators Voltage fluctuations Capacitors Distribution networks Switches Probabilistic logic

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A Lightweight AI Model for Anomaly Detection in Wireless Networks

A Lightweight AI Model for Anomaly Detection in Wireless Net...

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Artificial Intelligence, Blockchain, and Internet of Things (AIBThings), IEEE International Conference on

作者： Thomas J. Kopcho Mostafa M. Fouda Cameron J. Krome Department of Computer Science Idaho State University Pocatello ID Department of Electrical and Computer Engineering Idaho State University Pocatello ID AI Data & Visualization Idaho National Laboratory Idaho Falls ID

ISBN: (数字)9798331529529

ISBN: (纸本)9798331529536

Detecting network anomalies is critical for wireless network security and reliability. Traditional AI methods often require substantial computational resources, particularly when deployed on cloud servers, leading to increased network load and latency. In contrast, deploying AI models directly on end devices enables real-time data processing at the source, facilitating faster anomaly detection and mitigation. We propose a lightweight hierarchical AI model where initial inferences are made by a simple model and outputs confidence scores. Using a modified TOPSIS-based method, we determine an optimal confidence score threshold. Inferences below this threshold are forwarded to a more complex model for accurate analysis, reducing overall computational demands while maintaining high detection performance. Our approach is tested on a 5 G network dataset, demonstrating competitive performance compared to other anomaly detection models.

关键词： Computational modeling Wireless networks Real-time systems Servers Security Reliability Artificial intelligence Anomaly detection Load modeling Testing

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Fault-tolerant Mobile Service Offloading in Mobile Edge Computing

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IEEE Transactions on Automation Science and engineering 2025年

作者： Long, Tingyan Xia, Yunni Zhou, Mengchu Li, Jianqi Ma, Yong Ai-Turki, Yusuf Guizhou University School of Computer Science and Technology Guiyang550025 China Chongqing University College of Computer Science Chongqing400030 China New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States Global energy interconnection research institute Co. Ltd Beijing102209 China Jiangxi Normal University School of Computer and Information Engineering Nanchang China King Abdulaziz University K. A. Care Energy Research and Innovation Center The Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Faculty of Engineering Jeddah21589 Saudi Arabia

Mobile edge computing (MEC) is an evolving paradigm for rendering services through network-accessible resources deployed over Internet of Things (IoT) nodes at the edge. Nevertheless, an MEC environment usually employs thousands of physical machines connected via hundreds of switches/routers that communicate and coordinate to deliver computing service. In such complicated systems, faults caused by software, human errors, and hardware are often unavoidable. The edge of network presents a dynamic environment with great quantities of terminals, high mobility of mobile devices, heterogeneous applications, and intermittent traffic. In such an environment, MEC can suffer from unbalanced resource provisioning and interruptions of faults occurring at different levels, which further causes task faults and affects service quality. To address this challenge, this work proposes a novel fault-tolerant offloading method for handling faults by leveraging a reinforcement-learning-based service offloading decision model. The model synthesizes a Dueling Deep Q Network (DQN)-based algorithm for deciding user offloading behaviors and an adaptive checkpointing method for improving task execution reliability. For the purpose of model validation and comparison, extensive simulations are conducted. Numerical results clearly demonstrate that the proposed method is highly effective and outperforms existing methods. © 2004-2012 IEEE.

关键词： Mobile applications

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