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

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Knowledge-aware Graph Attention Network with distributed & Cross Learning for Collaborative Recommendation

Knowledge-aware Graph Attention Network with Distributed & C...

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IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Yang Dai Shunmei Meng Qiyan Liu Xiao Liu School of Cyberspace Security NanJing University of Science and Technology Nanjing China State Key Lab. for Novel Software Technology NanJing University Nanjing China University of Toronto Toronto Canada

Nowadays, side-information is widely used to rein-force the user-item interaction and helps to handle the sparsity issue and cold start problem of conventional recommendation algorithms. Due to the overlook of the relationship between items and entities and the higher-order connectivity information, most existing approaches are hard to get users' deep preferences. In this paper, we propose KGANCL, a Knowledge-aware Graph Attention Network with distributed & Cross Learning. It focuses on using different forms of the knowledge graph to strengthen both users' and items' embedding representations, respectively. Firstly, Graph Attention Network is adopted for user embedding learning, which can give different importance scores to different neighbors, and a user-item KG graph is used to integrate adjacent information to enhance the representation. Secondly, a cross module is used for item embedding learning, which shares the high-order interaction between the recommender system and the knowledge graph. We also use the idea of distributed processing for embeddings in different entities to improve the learning efficiency. Experimental results demonstrate that KGANCL can provide better recommendations compared with the state-of-the-art baseline models. Our model can also maintain superior prediction accuracy even in little-known interaction scenarios.

关键词： Adaptation models distributed processing Computational modeling Scalability Collaboration Knowledge graphs Computer architecture

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Fast parallel SVM based Arrhythmia Detection on Multiple GPU Clusters 10

Fast Parallel SVM based Arrhythmia Detection on Multiple GPU...

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10th IEEE international conference on Communication Systems and Network Technologies, CSNT 2021

作者： Latif, Ghazanfar Alghazo, Jaafar Butt, Mohsin Kazimi, Zafar A. Department of Computer Science Prince Mohammad Bin Fahd University -Khobar Saudi Arabia Department of Computer Engineering Prince Mohammad Bin Fahd University -Khobar Saudi Arabia Prep Computer Science Department King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Information Technology Prince Mohammad Bin Fahd University -Khobar Saudi Arabia

ISBN: (纸本)9780738105239

Regression analysis and classification can be done using a supervised learning technique called Support Vector Machine (SVM) which is one of many such methods. The method creates hyperplanes which are used to analyze data patterns and separate data into multiple classes. The computation complexity of the algorithm is very high for training and testing of large multidimensional datasets. In this work, we propose a scalable and cost-effective method to run SVM that reduces memory usage and computing power. The process uses distributed cloud GPU’s cluster nodes to run the algorithm in parallel on data which is divided into "n" parts. The results obtained from each of the cluster nodes are merged on a master node and the SVM algorithm is applied once more for classification. The study tackles the ECG classification using parallel SVM to investigate heartbeats and brain traces linked with different types of Arrhythmia and Seizure. Experiments performed on real ECG datasets (MIT BIH Diagnostic database and EEG Seizure database) resulted in a classification accuracy of 97.45%. The technique is proven both efficient by reducing training time and with high classification accuracy. The results achieved show that the proposed technique outperforms similar methods proposed in previous literature. © 2021 IEEE.

关键词： Electrocardiograms

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Detecting JVM JIT Compiler Bugs via Exploring Two-Dimensional Input Spaces

Detecting JVM JIT Compiler Bugs via Exploring Two-Dimensiona...

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international conference on Software Engineering (ICSE)

作者： Haoxiang Jia Ming Wen Zifan Xie Xiaochen Guo Rongxin Wu Maolin Sun Kang Chen Hai Jin School of Cyber Science and Engineering Huazhong University of Science and Technology China Hubei Key Laboratory of Distributed System Security Services Computing Technology and System Lab Cluster and Grid Computing Lab. Hubei Engineering Research Center on Big Data Security National Engineering Research Center for Big Data Technology and System School of Informatics Xiamen University China School of Computer Science and Technology Huazhong University of Science and Technology China

Java Virtual Machine (JVM) is the fundamental software system that supports the interpretation and execution of Java bytecode. To support the surging performance demands for the increasingly complex and large-scale Java programs, Just-In-Time (JIT) compiler was proposed to perform sophisticated runtime optimization. However, this inevitably induces various bugs, which are becoming more pervasive over the decades and can often cause significant consequences. To facilitate the design of effective and efficient testing techniques to detect JIT compiler bugs. This study first performs a preliminary study aiming to understand the characteristics of JIT compiler bugs and the corresponding triggering test cases. Inspired by the empirical findings, we propose JOpFuzzer, a new JVM testing approach with a specific focus on JIT compiler bugs. The main novelty of JOpFuzzer is embodied in three aspects. First, besides generating new seeds, JOpFuzzer also searches for diverse configurations along the new dimension of optimization options. Second, JOpFuzzer learns the correlations between various code features and different optimization options to guide the process of seed mutation and option exploration. Third, it leverages the profile data, which can reveal the program execution information, to guide the fuzzing process. Such nov-elties enable JOpFuzzer to effectively and efficiently explore the two-dimensional input spaces. Extensive evaluation shows that JOpFuzzer outperforms the state-of-the-art approaches in terms of the achieved code coverages. More importantly, it has detected 41 bugs in OpenJDK, and 25 of them have already been confirmed or fixed by the corresponding developers.

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An Extensible Software and Communication Platform for distributed Energy Resource Management

An Extensible Software and Communication Platform for Distri...

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2020 international conference on Communications Control and computing Technologies for Smart grids

作者： Fierro, Gabe Moffat, Keith Pakshong, Jasper von Meier, Alexandra Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA Univ Calif Berkeley Dept Civil & Environm Engn Berkeley CA USA Univ Calif Berkeley Calif Inst Energy & Environm Dept Elect Engn & Comp Sci Berkeley CA USA

ISBN: (纸本)9781728161273

This paper introduces a novel distributed Extensible grid Control (DEGC) software and communication platform to facilitate the control of distributed energy resources on electric grids. The DEGC software platform leverages state-of-the-art advances in secure, distributed communication and decentralized authorization and authentication. We discuss how these advances enable the kind of robust and secure communication required for a distributed grid control platform, and show how DEGC applies these technologies to the agile development and deployment of grid software through an extensible and flexible API. We describe how DEGC can implement both Volt-VAR voltage magnitude control and Phasor-Based Control as sample applications and demonstrate the DEGC platform in hardware with the demanding Phasor-Based Control test case, and provide performance metrics.

关键词： distributed control communication grid security phasor-based control

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A List-based Heuristic Algorithm for Static Task Scheduling in Heterogeneous distributed computing Systems 6

A List-based Heuristic Algorithm for Static Task Scheduling ...

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6th international conference on Web Research (ICWR)

作者： Gholami, Hadi Zakerian, Reza Islamic Azad Univ Ayatollah Amoli Branch Dept Comp Engn Amol Iran Tech & Vocat Univ Fac Mahmoudabad Dept Comp Engn Mazandaran Iran

ISBN: (纸本)9781728110516

Executing complicated computations in parallel increases the speed of computing and brings user delight to the system. Decomposing the program into several small programs and running multiple parallel processors are modeled by Directed Acyclic Graph. Scheduling nodes to execute this task graph is an important problem that will speed up computations. Since task scheduling in this graph belongs to NP-hard problems, various algorithms were developed for node scheduling to contribute to quality service delivery. The present study brought a heuristic algorithm named looking ahead sequencing algorithm (LASA) to cope with static scheduling in heterogeneous distributed computing systems with the intention of minimizing the schedule length of the user application. In the algorithm proposed here, looking ahead is considered as a criterion for prioritizing tasks. Also, a property called Emphasized Processor has been added to the algorithm to emphasize the task execution on a particular processor. The effectiveness of the algorithm was shown on few workflow type applications and the results of the algorithm implementation were compared with two more heuristic and meta-heuristic algorithms.

关键词： distributed computing Makespan Static Scheduling Workflow Scheduling

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Distribution Network Planning and Design Supported by PSO-AFSA Hybrid Optimization Algorithm

Distribution Network Planning and Design Supported by PSO-AF...

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international conference on Application of Intelligent Systems in Multi-modal Information Analytics, MMIA 2020

作者： Xun, Chao Zheng, Jieyun Lin, Keyao Lin, Tingting Xiao, Fen State Grid Fujian Electric Power Co. Ltd. FuzhouFujian350003 China Economic and Technical Research Institute State Grid Fujian Provincial Electric Power Co. Ltd. FuzhouFujian350012 China Institute of Economics and Technology State Grid Fujian Provincial Electric Power Co. Ltd. FuzhouFujian350012 China State Grid Fujian Nanjing County Power Supply Company NanjingFujian363600 China

ISBN: (纸本)9783030514303

From a scientific point of view, power grid planning is a very professional work, and subject to the impact of modern urban construction, this work is more difficult, and it has a highly constrained & discrete variable nonlinear integer programming problem. At the same time, the intelligent development of the power grid needs to continuously improve its reliable power supply and high-efficiency operation. Since the distribution network can change topology by changing the switch state, the distribution network is reconstructed to reasonably arrange the distributed grid connection to reduce the network loss. It is of great theoretical and practical significance to improve the node voltage deviation and realize the economic and safe operation of the distribution network considering DG. In this paper, the PSO-AFSA hybrid optimization algorithm model is analyzed firstly, its application in distribution network planning and design is discussed. The concrete nodes in the application of hybrid algorithm are calculated, the results show that the distribution of hybrid optimization algorithm is included in DG. The voltage deviation and active network loss of the network node are reduced, and the reliability of the power supply of the distribution network is guaranteed. © 2021, Springer Nature Switzerland AG.

关键词： Particle swarm optimization (PSO)

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parallel Finite Cell Method with Adaptive Geometric Multigrid 26th

Parallel Finite Cell Method with Adaptive Geometric Multigri...

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26th international conference on parallel and distributed computing (Euro-Par)

作者： Saberi, S. Vogel, A. Meschke, G. Ruhr Univ Bochum High Performance Comp Engn Sci Univ Str 150 D-44801 Bochum Germany Ruhr Univ Bochum Inst Struct Mech Univ Str 150 D-44801 Bochum Germany

ISBN: (纸本)9783030576752;9783030576745

Generation of appropriate computational meshes in the context of numerical methods for partial differential equations is technical and laborious and has motivated a class of advanced discretization methods commonly referred to as unfitted finite element methods. To this end, the finite cell method (FCM) combines high-order FEM, adaptive quadrature integration and weak imposition of boundary conditions to embed a physical domain into a structured background mesh. While unfortunate cut configurations in unfitted finite element methods lead to severely ill-conditioned system matrices that pose challenges to iterative solvers, such methods permit the use of optimized algorithms and data patterns in order to obtain a scalable implementation. In this work, we employ linear octrees for handling the finite cell discretization that allow for parallel scalability, adaptive refinement and efficient computation on the commonly regular background grid. We present a parallel adaptive geometric multigrid with Schwarz smoothers for the solution of the resultant system of the Laplace operator. We focus on exploiting the hierarchical nature of space tree data structures for the generation of the required multigrid spaces and discuss the scalable and robust extension of the methods across process interfaces. We present both the weak and strong scaling of our implementation up to more than a billion degrees of freedom on distributed-memory clusters.

关键词： Unfitted finite element Finite cell Geometric multigrid Massively parallel High-performance computing

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Effective Microgrid Cost Reduction using Dragon Fly Optimization Algorithm and Firefly Algorithm

Effective Microgrid Cost Reduction using Dragon Fly Optimiza...

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5th international conference on computing, Communication and Security (ICCCS)

作者： Kumari, Kavitha K. S. Babu, R. Samuel Rajesh Sathyabama Inst Sci & Technol Dept Elect & Elect Engn Chennai 600119 Tamil Nadu India Sathyabama Inst Sci & Technol Dept Elect & Instrumentat Engn Chennai 600119 Tamil Nadu India

ISBN: (纸本)9781728191805

Introducing distributed generation (DG) into distribution networks provide reliable power to the consumers. The dispatchable and non-dispatchable unit usually placed nearby distribution networks operates in medium/low voltage system. The dragonfly and firefly algorithm are used for micro grid optimal scheduling both in grid connected mode and island mode. Dispatchable and non-Dispatchable units in the micro grid are connected to the conventional grid to supply energy to the end user. The fire fly algorithm has a drawbacks to find the global minima and also they were not able to provide a proper balance between exploration and exploitation. The drawback of DA it does not give accurate optimal solution for multi-objective problem and it was not used for short term wind power prediction. To find the minimum operating cost of micro grid the protype is developed for Dragonfly and firefly algorithm. Comparative performance analyses are done with the results of DA and firefly algorithm. Here the Dragon fly algorithm outperforms firefly algorithm by evaluating with power demand and operating cost of micro grid

关键词： distributed energy resource islanded operation Dragon fly algorithm firefly algorithm

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Discrete Event Simulation in Cloud-Edge Manufacturing Environments: Performance, Energy and Cost Trade-offs

Discrete Event Simulation in Cloud-Edge Manufacturing Enviro...

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IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Moustafa Faheem Adrian Murphy Vishal Sharma Carlos Reaño Queen's University Belfast UK Universitat de València Spain

Escalating the performance of Discrete Event Simulations (DESs) in manufacturing factory environ-ments plays a valuable role towards harnessing their real-time predictive and analytical capabilities. However, this attraction of performance-enhancement, whilst justified, has often caused the oversight of examination into how other notable metrics such as energy -efficiency and Total Cost of Ownership (TCO) affect the feasibility of DES management and implementation in factories. Hence, this work investigates how a line-balancing DES combination of performance, energy and TCO varies between low-resource edge devices, high-resource edge devices and remote High Performance computing (HPC) clusters in the cloud. The findings demonstrate that, although an HPC cluster is noticeably more viable in terms of per-formance, it is not a consistently advantageous option for energy-efficiency and TCO. Alternately, we argue that a high-resource edge device displays itself as the preferred factory-appropriate hardware-choice to complement all three metrics-of-interest considered in this work.

关键词： Performance evaluation Energy consumption Costs High performance computing Production facilities Real-time systems Nanoscale devices

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Performance study of HPC applications on an Arm-based cluster using a generic efficiency model 28

Performance study of HPC applications on an Arm-based cluste...

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28th Euromicro international conference on parallel, distributed and Network-Based Processing (PDP)

作者： Banchelli, Fabio Peiro, Kilian Querol, Andrea Ramirez-Gargallo, Guillem Ramirez-Miranda, Guillem Vinyals, Joan Vizcaino, Pablo Garcia-Gasulla, Marta Mantovani, Filippo Barcelona Supercomp Ctr Barcelona Spain

ISBN: (纸本)9781728165820

HPC systems and parallel applications are increasing their complexity. Therefore the possibility of easily study and project at large scale the performance of scientific applications is of paramount importance. In this paper we describe a performance analysis method and we apply it to four complex HPC applications. We perform our study on a pre-production HPC system powered by the latest Arm-based CPUs for HPC, the Marvell ThunderX2. For each application we spot inefficiencies and factors that limit their scalability. The results show that in several cases the bottlenecks do not come from the hardware but from the way applications are programmed or the way the system software is configured.

关键词： Performance analysis High Performance computing parallel Applications Arm ThunderX2

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