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检索条件"任意字段=18th Workshop on Parallel and Distributed Simulation"

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LOW LATENCY TWO STAGE BEAMFORMING WIth distributed MICROPHONE ARRAYS USING A PLANE WAVE DECOMPOSITION 18

LOW LATENCY TWO STAGE BEAMFORMING WITH DISTRIBUTED MICROPHON...

引用

18th International workshop on Acoustic Signal Enhancement (IWAENC)

作者： Mittal, Manan Corey, Ryan M. Zhuang, Yongjie Singer, Andrew C. SUNY Stony Brook Stony Brook NY 11794 USA Univ Illinois Chicago IL USA Discovery Partners Inst Chicago IL USA

ISBN: (纸本)9798350361865;9798350361858

Many rooms are equipped with conferencing systems with a large number of microphones. However, these systems are often limited to a fixed number of delay-and-sum beamformers and typical automix software will pick the beamformer output with the most energy. A more constructive combination is possible if we have access to the output of multiple beams constructed by such commercial systems. this article proposes a beamspace projection that may effectively view such a commercial conferencing system as a low-latency dimensionality reduction operation. Such a projection can be formulated as a plane wave decomposition of the received signals. Experiments conducted in simulation show that beamspace projection can rapidly approach the SINR gain achievable with access to all the microphones with lower computational complexity. Finally, we use commercial hardware and its beamformer outputs to separate numerous talkers in a real world environment.

关键词： Plane Wave Decomposition Beamforming Microphone Arrays Sensor Networks

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An Approach to Improving Reliability of parallel Graph Computation 18th

An Approach to Improving Reliability of Parallel Graph Compu...

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18th International Conference on theoretical Aspects of Software Engineering (TASE)

作者： Cui, Jin Duan, Zhenhua Xian Shiyou Univ Xian 710065 Peoples R China Xidian Univ ICTT & ISN Lab Xian 710071 Peoples R China

ISBN: (纸本)9783031646256;9783031646263

the distributed programming framework for parallel graph computation has been proposed to process and analyze large scale graph data. However, how to model and verify properties of parallel graph computation deserves our attention and studying so as to improve the reliability of big data processing. In this paper, we propose an approach based on runtime verification at code level to verify properties of the parallel graph computation process. With this approach, the parallel computation framework Pregel for graph data processing is modeled in MSVL (Modeling, simulation and Verification Language), a property to be verified is specified by a PPTL (Propositional Projection Temporal Logic) formula, then a compiler MCII is employed to verify whether a property is satisfied. Case studies of the shortest path problem and PageRank algorithm are conducted to demonstrate our approach.

关键词： Runtime verification at code level parallel graph computation MSVL Reliability

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A social network and simulation-based optimization approach for manufacturing resilience in a distributed manufacturing system 57

A social network and simulation-based optimization approach ...

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18th IFAC workshop on Time Delay Systems, TDS 2024

作者： Manupati, Vijaya Kumar Putnik, Goran Jacob, Sandra Mary Chiramal, Ashik Anto Sooraj, N.R. Operations and Supply chain Management Indian Institute of Management Mumbai400087 India School of Engineering University of Minho Campus de Azurém Guimarães4800-058 Portugal

Manufacturing systems in the distributed environment are becoming increasingly complex and challenging to manage as a result of contemporary client requirements, such as mass individualization, highly customized, and sustainable products. However, loss of production caused by a multitude of risks and disruptions, in addition to the aforementioned issues, necessitates the establishment of a resilient system. Rendering the ability of a system to respond and recovery from these disruptions to achieve manufacturing resilience need effective production planning and scheduling strategies. In this paper, we define Time to Survive (TTS) and Time to Recovery (TTR) and throughput loss as a metrics to aid the robust and recovery phases of developing a resilient distributed manufacturing system. A social network analysis based simulation approach is developed to assess the performance of pre- and post-disruption scenarios. Specifically, we investigate the complex distributed manufacturing system by disrupting the identified critical machines/enterprises and its effects on system performance. Numerical case studies are being undertaken to study the effects of disrupted firms on distributed manufacturing system performance by using simulation and optimization approach, as well as how rescheduling of process planning and scheduling affects performance measures like as system configurations, robustness, and resilience. © 2024 the Authors.

关键词： Recovery

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distributed Reactive Power Control Scheme for parallel Inverters Based on Virtual Impedance 1

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18th Annual Conference of China Electrotechnical Society, ACCES 2023

作者： Ma, Rui Fan, Hui Li, Jianfeng Hao, Xiaoguang Hu, Changbin Luo, Shanna State Grid Hebei Electric Power Research Institute Shijiazhuang050021 China State Grid Hebei Electric Power Company Shijiazhuang050021 China School of Electrical and Control Engineering North China University of Technology Beijing100144 China

ISBN: (数字)9789819710720

ISBN: (纸本)9789819710713

Droop control is an important control strategy for microgrids with multiple inverters in parallel. Adding virtual impedance to droop control can effectively increase the voltage of the common coupling point and achieve equal sharing of reactive power. However, in practical engineering, due to line aging and environmental changing, line parameters will change, which will affect the traditional virtual impedance control performance, making it difficult to divide reactive power accurately. To address this issue, we propose a distributed optimization compensation control scheme based on dynamic virtual impedance. Using the reactive power output by an inverter as a communication signal, based on the multi-agent consensus, we optimize the virtual impedance, which effectively compensates the influence of line impedance mismatch, realizes the uniform sharing of load reactive power, and compensates the line voltage drop. When the line parameters change due to the factors such as aging and damage, the scheme can still realize the uniform share of reactive power and compensate the voltage drop on the line. the addition of secondary regulation to the droop control can significantly suppress the variations of the bus voltage and frequency when the load changes. the effectiveness of the scheme is verified by the MATLAB/Simulink simulation software and a RTDS-based hardware-in-the-loop simulation platform. © Beijing Paike Culture Commu. Co., Ltd. 2024.

关键词： Reactive power

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Collaborative Scheduling of Multi-cloud distributed Multi-cloud Tasks Based on Evolutionary Multi-tasking Algorithm 18th

Collaborative Scheduling of Multi-cloud Distributed Multi-cl...

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18th International Conference on Bio-Inspired Computing: theories and Applications (BIC-TA)

作者： Zhao, Tianhao Wu, Linjie Cui, Zhihua Cai, Xingjuan Taiyuan Univ Sci & Technol Shanxi Lab Big Data Anal & Parallel Comp Taiyuan 030024 Peoples R China

ISBN: (纸本)9789819722716;9789819722723

With the rapid development of information technology making the scale of the Internet increasing day by day, collaborative optimization of multiple scheduling tasks in a multi-cloud environment provides users with faster scheduling options. Meanwhile, there is a certain similarity between cloud scheduling tasks, and in order not to waste the similarity between tasks, similar tasks are linked together to find an optimal scheduling solution for multiple tasks, making it possible to handle multiple scheduling tasks simultaneously. Firstly, we construct a multi-objective optimization model considering time, cost and VM resource load balance;secondly, since there are not only independent optimization problems in real scenarios, we adapt the constructed multiple similar optimization models and propose a multi-task multi-objective optimization model;finally, to be able to solve the constructed model better, we use a proposed objective function-based Finally, we propose an evolutionary multitasking algorithm based on weighted summation of the objective functions, which allows the algorithm to find the optimal solution among multiple multi-objective models. simulation experiments show that the proposed algorithm has better performance.

关键词： Evolutionary Multitasking algorithm Task scheduling Cloud Computing Optimization

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Recommendation-Aware Collaborative Edge Caching Strategy in the Internet of Vehicles 18th

Recommendation-Aware Collaborative Edge Caching Strategy in...

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18th International Conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2024

作者： Ou, Pingjie Chen, Ningjiang Huang, Zizhan School of Computer and Electronic Information Guangxi University Guangxi Nanning530004 China Key Laboratory of Parallel Distributed and Intelligent Computing Education Department of Guangxi Zhuang Autonomous Region Guangxi University Guangxi Nanning530004 China

ISBN: (纸本)9783031714696

Due to the limited resources of edge networks, the heterogeneity of user content requests, high-cost caching from direct resource hits, and redundancy in resource retention time hinder system performance. Traditional caching methods based on learning and popularity tend to encounter data skew when handling vehicle requests, leading to untimely cache data updates. To address these issues, this paper proposes an efficient edge cooperative caching strategy with recommendation awareness. Firstly, a time series prediction model based on a multi-dense multilayer perceptron is designed. this model segments historical request information into sub-sequence level slivers to enhance positional correlations between information, predicting user requests through historical time series and covariates. Secondly, to optimize cache utilization, comprehensively considers user mobility and contribution to enable recommendation awareness. Additionally, an optimized lifecycle is introduced to design a cache replacement strategy. simulation experiments demonstrate that, compared to caching schemes based on content popularity and deep reinforcement learning, the proposed method achieves lower caching costs and higher cache hit rates. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep reinforcement learning

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18th IFIP WG 10.3 International Conference on Network and parallel Computing, NPC 2021

18th IFIP WG 10.3 International Conference on Network and Pa...

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18th IFIP WG 10.3 International Conference on Network and parallel Computing, NPC 2021

ISBN: (纸本)9783030935702

the proceedings contain 20 papers. the special focus in this conference is on Network and parallel Computing. the topics include: A Novel Task-Allocation Framework Based on Decision-Tree Classification Algorithm in MEC;qoS-Aware Scheduling for Cellular Networks Using Deep Reinforcement Learning;preface;High Resolution of City-Level Climate simulation by GPU with Multi-physical Phenomena;Adaptive Buffering Scheme for PCM/DRAM-Based Hybrid Memory Architecture;efficiency-First Fault-Tolerant Replica Scheduling Strategy for Reliability Constrained Cloud Application;Towards an Optimized Containerization of HPC Job Schedulers Based on Namespaces;architecture of an On-Time Data Transfer Framework in Cooperation with Scheduler System;data Delta Based Hybrid Writes for Erasure-Coded Storage Systems;BDCuckoo: an Efficient Cuckoo Hash for Block Device;A Two Tier Hybrid Metadata Management Mechanism for NVM Storage System;A Novel CFLRU-Based Cache Management Approach for NAND-Based SSDs;taming Congestion and Latency in Low-Diameter High-Performance Datacenters;evaluation of Topology-Aware All-Reduce Algorithm for Dragonfly Networks;dgQuEST: Accelerating Large Scale Quantum Circuit simulation through Hybrid CPU-GPU Memory Hierarchies;MPICC: Multi-Path INT-Based Congestion Control in Datacenter Networks;vSketchDLC: A Sketch on distributed Deep Learning Communication via Fine-grained Tracing Visualization;Scalable Algorithms Using Sparse Storage for parallel Spectral Clustering on GPU.

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11th Mining Humanistic Data workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st workshop/Special Session on Machine Learning and Big Data in Health Care, ML@HC 2022 and 2nd workshop on Artificial Intelligence in Biomedical Engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022

11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putt...

引用

11th Mining Humanistic Data workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st workshop/Special Session on Machine Learning and Big Data in Health Care, ML@HC 2022 and 2nd workshop on Artificial Intelligence in Biomedical Engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022

ISBN: (纸本)9783031083402

the proceedings contain 35 papers. the special focus in this conference is on Mining Humanistic Data. the topics include: Digitally Assisted Planning and Monitoring of Supportive Recommendations in Cancer Patients;CAIPI in Practice: Towards Explainable Interactive Medical Image Classification;a Deep Q Network-Based Multi-connectivity Algorithm for Heterogeneous 4G/5G Cellular Systems;simulating Blockchain Consensus Protocols in Julia: Proof of Work vs Proof of Stake;Maximum Likelihood Estimators on MCMC Sampling Algorithms for Decision Making;employing Natural Language Processing Techniques for Online Job Vacancies Classification;Probabilistic Quantile Multi-step Forecasting of Energy Market Prices: A UK Case Study;proactive Buildings: A Prescriptive Maintenance Approach;performance Meta-analysis for Big-Data Univariate Auto-Imputation in the Building Sector;non-intrusive Diagnostics for Legacy Heat-Pump Performance Degradation;a 5G-Based Architecture for Localization Accuracy;anomaly Detection in Small-Scale Industrial and Household Appliances;an Innovative Software Platform for Efficient Energy, Environmental and Cost Planning in Buildings Retrofitting;deep Learning-Based Segmentation of the Atherosclerotic Carotid Plaque in Ultrasonic Images;An Intelligent Grammar-Based Platform for RNA H-type Pseudoknot Prediction;An Automated 2D U-Net Segmentation Method for the Identification of Cancer Brain Metastases Using MRI Images;the Use of Robotics in Critical Use Cases: the 5G-ERA Project Solution;fundamental Features of the Smart5Grid Platform Towards Realizing 5G Implementation;experimentation Scenarios for Machine Learning-Based Resource Management;efficient Data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases;5G for the Support of Smart Power Grids: Millisecond Level Precise distributed Generation Monitoring and Real-Time Wide Area Monitoring;monitoring Neurological Disorder Patients via Deep Learning Based Facial Expressions An

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One-Shot distributed Node-Specific Signal Estimation with Non-Overlapping Latent Subspaces in Acoustic Sensor Networks

One-Shot Distributed Node-Specific Signal Estimation with No...

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International workshop on Acoustic Signal Enhancement (IWAENC)

作者： Paul Didier Pourya Behmandpoor Toon van Waterschoot Marc Moonen Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Belgium

ISBN: (数字)9798350361858

ISBN: (纸本)9798350361865

A one-shot algorithm called iterationless DANSE (iDANSE) is introduced to perform distributed adaptive node-specific signal estimation (DANSE) in a fully connected wireless acoustic sensor network (WASN) deployed in an environment with non-overlapping latent signal subspaces. the iDANSE algorithm matches the performance of a centralized algorithm in a single processing cycle while devices exchange fused versions of their multichannel local microphone signals. Key iterationless nature, which favors deployment in real-time applications, and the fact that devices can exchange fewer fused signals than the number of latent sources in the environment. the proposed method is validated in numerical simulations including a speech enhancement scenario.

关键词： Performance evaluation Wireless communication Wireless sensor networks Conferences Estimation Speech enhancement Acoustic sensors Numerical simulation Real-time systems Microphones

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Towards Efficient Remote OpenMP Offloading 18th

Towards Efficient Remote OpenMP Offloading

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18th International workshop on OpenMP (IWOMP)

作者： Lu, Wenbin Shan, Baodi Raut, Eric Meng, Jie Araya-Polo, Mauricio Doerfert, Johannes Malik, Abid M. Chapman, Barbara SUNY Stony Brook Stony Brook NY 11794 USA TotalEnergies EP R&T Houston TX 77002 USA Argonne Natl Lab Lemont IL 60439 USA Brookhaven Natl Lab Upton NY 11793 USA

ISBN: (纸本)9783031159220;9783031159213

On modern heterogeneous HPC systems, the most popular way to realize distributed computation is the hybrid programming model of MPI+X (X being OpenMP/CUDA/etc.), as it has been proven to perform well with various scientific applications. However, application developers prefer to use a single coherent programming model over a hybrid model, as maintainability and portability decrease per additional model. Recent work [14] has shown that the OpenMP device offloading model could be used to program distributed accelerator-based HPC systems with minimal changes to the application. In this paper, we improve the performance of OpenMP remote offloading through various runtime optimizations, guided by a detailed overhead analysis. Evaluation of our work is conducted using an industrial-level seismic modeling code, Minimod, as well as two proxy-apps, XSBench and RSBench. Results show that, compared to the baseline version, our optimizations can reduce offloading latencies by up to 92%, and raise application parallel efficiency by at least 25.2% when running with 16 GPUs. We then point out why strong scaling is still difficult with OpenMP remote offloading, and propose further improvements to the runtime to increase scalability.

关键词： OpenMP GPGPU distributed computing

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