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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

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4th international conference on Ubiquitous Communications and Network computing, UBICNET 2021

4th International Conference on Ubiquitous Communications an...

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4th international conference on Ubiquitous Communications and Network computing, UBICNET 2021

ISBN: (纸本)9783030792756

The proceedings contain 17 papers. The special focus in this conference is on Ubiquitous Communications and Network computing. The topics include: Predictive Modeling of the Spread of COVID-19: The Case of India;ASIF: An Internal Representation Suitable for Program Transformation and parallel Conversion;Performance Comparison of VM Allocation and Selection Policies in an Integrated Fog-Cloud Environment;Fraud Detection in Credit Card Transaction Using ANN and SVM;detection of Leukemia Using K-Means Clustering and Machine Learning;an Analysis and Implementation of a Deep Learning Model for Image Steganography;abstractive Text Summarization on Templatized Data;mobility Management Based Mode Selection for the Next Generation Network;specification of a Framework, Fully distributed, for the Management of All Types of Data and the Services Close to Users;A Leading Edge Detection Algorithm for UWB Based Indoor Positioning Systems;designing Multiband Millimeter Wave Antenna for 5G and Beyond;analog Beamforming mm-Wave Two User Non-Orthogonal Multiple Access;A Novel Multi-User Quantum Communication System Using CDMA and Quantum Fourier Transform;Qubit Share Multiple Access Scheme (QSMA);Design of CoAP Based Model for Monitoring and Controlling Physical Parameters.

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OpenMP automatic translation framework for Sunway TaihuLight 3

OpenMP automatic translation framework for Sunway TaihuLight

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3rd IEEE international conference on Communications, Information System and Computer Engineering, CISCE 2021

作者： Li, Mingliang Pang, Jianmin Yue, Feng Wang, Qihan State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou China

ISBN: (纸本)9780738112152

The Sunway processor is a unique heterogeneous many-core processor used by Sunway TaihuLight supercomputer. However, developing parallel programs on the Sunway processor is still complex. In this paper, a source-to-source translation framework for the Sunway heterogeneous many-core processors is designed and implemented, which can transform OpenMP programs into many-core accelerated programs amenable to the Sunway architecture. Considering differences between the OpenMP shared-memory programming model and the Sunway programming model, a translation model has been proposed for converting OpenMP programs. A set of runtime functions based on the Sunway architecture has been implemented, including a tree-based reduction algorithm and an effective distributed lock mechanism. The experimental results show that the translation framework can correctly translate OpenMP programs, and the proposed lock mechanism reduces the overhead by up to 90% against the baseline. © 2021 IEEE.

关键词： Supercomputers

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Matching Theory Aided Federated Learning Method for Load Forecasting of Virtual Power Plant 17

Matching Theory Aided Federated Learning Method for Load For...

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17th IEEE international conference on Mobility, Sensing and Networking (MSN)

作者： Yan, Min Wang, Li Wang, Xuanyuan Li, Liang Xu, Lianming Fei, Aiguo Beijing Univ Posts & Telecommun Sch Comp Sci Natl Pilot Software Engn Sch Beijing 100876 Peoples R China State Grid Jibei Elect Power Co Ltd Beijing 100054 Peoples R China Beijing Univ Posts & Telecommun Sch Elect Engn Beijing 100876 Peoples R China

ISBN: (纸本)9781665406680

As an emerging distributed learning paradigm, Federated Learning (FL) allows smart meters to collaboratively train a load forecasting model while keeping their private data on local devices. However, two critical issues hinder the deployment of ordinary FL algorithm in load forecasting: (i) one global model cannot fit all users well due to their heterogeneous load patterns;(ii) the training speed of FL severely depends on a few stragglers with scarce communication and computing resources. In this work, we propose a novel multi-center FL framework for load forecasting to learn multiple models simultaneously by grouping the users according to their model dissimilarity and training time. Specifically, a problem is formulated to jointly optimize the grouping strategy and forecasting model parameters, which is resolved by integrating the matching algorithm into the update process of model parameters in FL. Simulation results on real load data show that, compared with the existing load forecasting methods based on FL, the prediction error of our scheme is reduced by 8.11%, and the training time is reduced by 90.37%.

关键词： Load Forecasting Federated Learning Matching Theory Virtual Power Plant

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Joint Service Placement and Computation Offloading in Mobile Edge computing: An Auction-based Approach 26

Joint Service Placement and Computation Offloading in Mobile...

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26th IEEE international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Zhang, Lei Qu, Zhihao Ye, Baoliu Tang, Bin Nanjing Univ Natl Key Lab Novel Software Technol Nanjing Peoples R China Hohai Univ Nanjing Peoples R China

ISBN: (纸本)9781728190747

The emerging applications, e.g, virtual reality, online games, and Internet of Vehicles, have computation-intensive and latency-sensitive requirements. Mobile edge computing (MEC) is a powerful paradigm that significantly improves the quality of service (QoS), of these applications by offloading computation and deploying services at the network edge. Existing works on service placement in MEC usually ignore the impact of the different requirements of QoS among service providers (SPs), which is common in many applications such that online game requires extremely low latency and online video requires extremely large bandwidth. Considering the competitive relationship among SPs, we propose an auction-based resource allocation mechanism. We formulate the problem as a social welfare maximization problem to maximize effectiveness of allocated resources while maintaining economic robustness. According to our theoretical analysis, this problem is NP-hard, and thus it is practically impossible to derive the optimal solution. To tackle this, we design multiple rounds of iterative auctions mechanism (MRIAM), which divides resources into blocks and allocates them through multiple rounds of auctions. Finally, we conduct extensive experiments and demonstrate that our auction-based mechanism is effective in resource allocation and robust in economics.

关键词： Mobile edge computing service placement auction theory computing offloading quality of service

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Research of Virtual Impedance Control Strategy of Hybrid Renewable Energy Microgrid 2020

Research of Virtual Impedance Control Strategy of Hybrid Ren...

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7th international conference on Automation and Logistics, ICAL 2020

作者： Yu, Qingguang Jiang, Zhicheng Zhao, Mengchu State Key Laboratory of Power System Department of Electrical Engineering Tsinghua University Beijing China State Grid Beijing Urban District Power Supply Company Beijing China

ISBN: (纸本)9781450377263

The principle of virtual impedance is analyzed in detail, and the simulation of parallel connection of inverter with different capacity is compared and analyzed in detail. The principle of virtual impedance is analyzed, and its derivation and analysis are carried out in detail. The simulation results show that the reactive power of parallel inverters with different capacities without virtual impedance cannot be distributed proportionally, and there is a large reactive circulation between inverters, which seriously threatens the safe and stable operation of micro grid. After the introduction of virtual impedance, reactive power distribution can be effectively improved, and the distribution effect is better with the increase of virtual impedance, but it will cause voltage sag of AC bus. This paper introduced the virtual impedance into the traditional droop control, make the output impedance and line impedance of the inverter are mainly inductive, so the droop control algorithm is implemented. This paper presented a new method based on the virtual impedance to adjust the frequency and voltage of the micro-grid bus to realize the adjustment of the voltage of the micro grid. © 2020 ACM.

关键词： Electric inverters

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A Novel Classification Model to Predict Batch Job Failures in Co-located Cloud 26

A Novel Classification Model to Predict Batch Job Failures i...

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26th IEEE international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Li, Yurui Lin, Weiwei Li, Keqin Wang, James Z. Liu, Fagui Liu, Jie South China Univ Technol Sch Comp Sci & Engn Guangzhou Peoples R China State Univ New York New Paltz Dept Comp Sci New Paltz NY 12561 USA Scutech Corp Co Ltd Guangzhou Peoples R China

ISBN: (纸本)9781728190747

Nowadays, cloud co-location is often used for data centers to improve the utilization of computing resources. However, batch jobs in a Co-location Datacenter (CLD) are vulnerable to failures due to the competition for limited resources with online service jobs. Such failed batch jobs would be rescheduled and failed repeatedly, resulting in the waste of computing resources and instability of the computing clusters. Therefore, we propose a method to accurately predict the potential failures of batch jobs for CLD. The core of the proposed method is STLF (SMOTE Tomek and LightGBM [5] Framework), which is divided into three parts. First, we use the co-feature extraction method to generate Co-located Feature Dataset (CLFD). Then SMOTE Tomek is used to oversampling the CLFD to ensure that the classifier can learn more minority features. Finally, we use LightGBM classifier to predict batch jobs' failure. The performance experiments conducted on the Ali Trace 2018 dataset show that our proposed STLF significantly outperforms the existing popular classifiers in terms of the ROC curve, the area under the ROC curve (AUC), precision, and recall.

关键词： cloud computing co-located datacenter failure prediction resource efficiency datacenter

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Synchronization Overlap Trade-Off for a Model of Spatial Distribution of Species 21st

Synchronization Overlap Trade-Off for a Model of Spatial Dis...

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21st international conference on Computational Science and Its Applications (ICCSA)

作者： Bioco, Joao Prata, Paula Canovas, Fernando Fazendeiro, Paulo Univ Beira Interior UBI Covilha Portugal Univ Beira Interior C4 Ctr Competencias Cloud Comp C4 UBI Covilha Portugal Univ Catolica San Antonio Murcia Fac Ciencias Salud Murcia Spain Inst Telecomunicacoes IT Covilha Covilha Portugal

ISBN: (纸本)9783030869601;9783030869595

Despite of the widespread implementation of agent-based models in ecological modeling and another several areas, modelers have been concerned by the time consuming of these type of models. This paper presents a strategy to parallelize an agent-based model of spatial distribution of biological species, operating in a multi-stage synchronous distributed memory mode, as a way to obtain gains in the performance while reducing the need for synchronization. A multiprocessing implementation divides the environment (a rectangular grid corresponding to the study area) into stage-subsets, according to the number of defined or available processes. In order to ensure that there is no information loss, each stage-subset is extended with an overlapping section from each one of its neighbouring stage-subsets. The effect of the size of this overlapping on the quality of the simulations is studied. These results seem to indicate that it is possible to establish an optimal trade-off between the level of redundancy and the synchronization frequency. The reported paralellization method was tested in a standalone multicore machine but may be seamlessly scalable to a computation cluster.

关键词： parallel programming Multiprocessing Agent-based modelling and simulation Synchronization-reducing algorithms

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ODCP: Optimizing Data Caching and Placement in distributed File System Using Erasure Coding 17th

ODCP: Optimizing Data Caching and Placement in Distributed F...

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17th IFIP WG 10.3 international conference on Network and parallel computing, NPC 2020

作者： Wu, Shuhan Li, Yunchun Yang, Hailong Luan, Zerong Li, Wei School of Computer Science and Engineering Beihang University Beijing100191 China College of Life Sciences and Bioengineering Beijing University of Technology Beijing100083 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi214125 China

ISBN: (纸本)9783030794774

Many current distributed file systems use erasure-coding based data redundancy techniques to improve the reliability of data storage. Such techniques can significantly improve the effective storage utilization. However, there are several drawbacks to the above techniques. Firstly, they introduce non-negligible computation overhead for decoding. Secondly, traditional data caching and placement strategies become less effective in such cases. To solve the above drawbacks, this paper proposes a new data cache allocation mechanism based on simulated annealing and a new data placement strategy based on convex optimization, which effectively reduces data block transmission delay and decoding delay. We have implemented the proposed data placement strategy in the real-world distributed file system Alluxio, and evaluated the performance of our strategy. Experiment results show that our strategy can significantly reduce the file read delay compared to traditional data placement strategies. © 2021, IFIP international Federation for Information Processing.

关键词： Convex optimization

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Quantum Annealing Approach for the Optimal Real- time Traffic Control using QUBO

Quantum Annealing Approach for the Optimal Real- time Traffi...

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22nd IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD-Fall)

作者： Singh, Amit Lin, Chun-Yu Huang, Chung-, I Lin, Fang-Pang Natl Appl Res Labs Natl Ctr High Performance Comp Hsinchu 300 Taiwan Natl Yang Ming Chiao Tung Univ Dept Mech Engn Hsinchu 300 Taiwan

ISBN: (纸本)9781665404037

Traffic congestion is one of the major issues in urban areas, particularly when traffic loads exceed the road's capacity, resulting in higher petrol consumption and carbon emissions as well as delays and stress for road users. In Asia, the traffic situation can be further deteriorated by road sharing of scooters. How to control the traffic flow to mitigate the congestion has been one of the central issues in transportation research. In this study, we employ a quantum annealing approach to optimize the traffic signals control at a real-life intersection with mixed traffic flows of vehicles and scooters. Considering traffic flow is a continuous and emerging phenomenon, we used quadratic unconstrained binary optimization (QUBO) formalism for traffic optimization, which has a natural equivalence to the Ising model and can be solved efficiently on the quantum annealers, quantum computers or digital annealers. In this article, we first applied the QUBO traffic optimization to artificially generated traffic for a simple intersection, and then we used real-time traffic data to simulate a real "Dongda-Keyuan" intersection with dedicated cars and scooter lanes, as well as mixed scooter and car lanes. We introduced two types of traffic light control systems for traffic optimization: C-QUBO and QUBO. Our rigorous QUBO optimizations show that C-QUBO and QUBO outperform the commonly used fixed cycle method, with QUBO outperforming C-QUBO in some instances. It has been found that QUBO optimization significantly relieves traffic congestion for the unbalanced traffic volume. Furthermore, we found that dynamic changes in traffic light signal duration greatly reduce traffic congestion.

关键词： real-time optimization traffic optimization traffic signal control quantum annealing quantum computing QUBO

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Cu-T-Pi Revised: An Updated Model Supercomputer for parallel computing Pedagogy 2nd

Cu-T-Pi Revised: An Updated Model Supercomputer for Parallel...

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22nd international conference on Interactive Collaborative Learning (ICL) / 48th IGIP international conference on Engineering Pedagogy - Impact of the 4th Industrial Revolution on Engineering Education

作者： Wolfer, James Indiana Univ South Bend IN 46615 USA

ISBN: (纸本)9783030402716;9783030402709

Cu-T-Pi, named for the CUDA, Nvidia TK1, and Raspberry N technology included, is a heterogeneous model supercomputer. Used as a pedagogic tool for teaching high-performance parallel computing, this model supports the major programming paradigms used in modern supercomputing. This work describes a complete remake of the original computer as a hardware and performance refresh, along with augmentation to support embedded Deep Learning.

关键词： High-Performance computing parallel computing Hardware model Deep-learning inference Pedagogy

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