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An simple and efficient fault tolerance mechanism for divide-and-conquer systems 04

An simple and efficient fault tolerance mechanism for divide...

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IEEE/ACM international symposium on Cluster Computing and the Grid (CCGRID)

作者： G. Wrzesinska R.V. van Nieuwpoort J. Maassen H.E. Bal Department of Mathematics and Computer Science Vrije Universiteit Amsterdam Amsterdam Netherlands

ISBN: (纸本)9780780384309

Summary form only given. We study if fault tolerance can be made simpler and more efficient by exploiting the structure of the application. More specifically, we study divide-and-conquer parallelism, which is a popular and effective paradigm for writing parallel Grid applications. We have designed a novel fault tolerance mechanism for divide-and-conquer applications that reduces the amount of redundant computation by storing results of the discarded in a global (replicated) table. These results can later be reused, thereby minimizing the amount of work lost as a result of a crash. The execution time overhead of our mechanism is close to zero. Our mechanism can handle crashes of multiple processors or entire clusters at the same time.. It can also handle crashes of the root node that initially started the parallel computation. We have incorporated our fault tolerance mechanism in Satin, which is a Java-based divide-and-conquer system. Satin is implemented on top of the Ibis communication library. The core of Ibis is implemented in pure Java, without using any native libraries. The Satin runtime system and our fault tolerance extension also are written entirely in Java. The resulting system therefore is highly portable allowing the software to run unmodified on a heterogeneous Grid. We evaluated the performance of our fault tolerance scheme on a cluster of the distributed ASCI Supercomputer 2 (DAS-2). In the first part of our tests, we show that the execution time overhead of our mechanism is close to zero. The results of the second part of our tests show that our algorithm salvages most of the work done by alive processors. Finally, we carried out tests on the European GridLab testbed. We ran one of our applications on a set of six heterogeneous parallel machines (four different operating systems, four different architectures) located in four different European countries. After manually killing one of the sites, the program recovered and finished normally.

关键词： Fault tolerant systems Testing Fault tolerance Computer crashes Java Software libraries parallel processing Writing Concurrent computing Supercomputers

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Predictable Efficiency for Reconfiguration of Service-Oriented Systems with Concerto

Predictable Efficiency for Reconfiguration of Service-Orient...

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IEEE/ACM international symposium on Cluster Computing and the Grid (CCGRID)

作者： Maverick Chardet Hélène Coullon Christian Perez Inria LS2N UBL IMT Atlantique Nantes France Inria CNRS ENS de Lyon UCBL LIP Univ. Lyon Lyon Cedex 07 France

ISBN: (数字)9781728160955

ISBN: (纸本)9781728196497

Dynamic reconfiguration of distributed software systems is nowadays gaining interest because of the emergence of dynamic IoT and smart applications as well as large scale dynamic infrastructures (e.g., Fog and Edge computing). When quality of service and experience is of prime importance, efficient reconfiguration is necessary, as well as performance predictability to decide when a reconfiguration should occur. This paper tackles the problem of efficient execution of a reconfiguration plan and its predictability with Concerto, a reconfiguration model supporting a high level of parallelism. Evaluation performed on synthetic cases and on two real production scenarios show that Concerto provides better performance than state-of- the-art systems with accurate time estimation.

关键词： parallel processing Tools Servers Software systems Estimation Planning

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Simulating heterogeneous models on multi-core platforms using Julia's computing language parallel potential 20

Simulating heterogeneous models on multi-core platforms usin...

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Proceedings of the IEEE/ACM 24th international symposium on distributed Simulation and Real Time applications

作者： Sergey Suslov Michael Schiek Markus Robens Christian Grewing Stefan van Waasen ZEA-2 - Electronic Systems Germany

This paper addresses the questions of high-level system modelling using heterogeneous multi-tool modelling environment on parallel multi-core processing systems for simulation acceleration. The modelling technique has been applied for high-level validation of a high-precision Indoor Positioning System for Motion Analysis (IPS-MA) developed in the Central Institute Electronic Systems (ZEA-2) of the Research Center Juelich GmbH. The heterogeneous modelling environment has been built using an implementation-level model designed in Matlab Simulink, a verification model for describing the system environment using Modelica language, and Julia language for automatic generation of binding modelling environment and parallelizing the simulation of the overall model. The approach showed a good flexibility in system description and verification in the multi-instrument modelling environment and a good performance gain due to simulation parallelism.

关键词： modelica Julia computing language high level system modelling parallelized simulation distributed simulation functional verification

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An Efficient Secure Coded Edge Computing Scheme Using Orthogonal Vector

An Efficient Secure Coded Edge Computing Scheme Using Orthog...

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IEEE international Conference on Big Data and Cloud Computing (BdCloud)

作者： Wei Zhou Jin Wang Lingzhi Li Jianping Wang Kejie Lu Xiaobo Zhou Computer Science and Technology Soochow University Suzhou P.R.China Computer Science City University of Hong Kong Hong Kong Computer Science and Engineering University of Puerto Rico at Mayaguez Mayaguez Puerto Rico Computer Science and Technology Tianjin University Tianjin P.R.China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

In recent years, Edge Computing (EC) has attracted increasing attention for its advantages in handling latencysensitive and compute-intensive applications. It is becoming a widespread solution to solve the last mile problem of cloud computing. However, in actual EC deployments, data confidentiality becomes an unignorable issue because edge devices may be untrusted. In this paper, a secure and efficient edge computing scheme based on linear coding is proposed. Generally, linear coding can be utilized to achieve data confidentiality by encoding random blocks with original data blocks before they are distributed to unreliable edge nodes. However, the addition of a large amount of irrelevant random blocks also brings great communication overhead and high decoding complexities. In this paper, we focus on the design of secure coded edge computing using orthogonal vector to protect the information theoretic security of the data matrix stored on edge nodes and the input matrix uploaded by the user device, while to further reduce the communication overhead and decoding complexities. In recent years, Edge Computing (EC) has attracted increasing attention for its advantages in handling latencysensitive and compute-intensive applications. It is becoming a widespread solution to solve the last mile problem of cloud computing. However, in actual EC deployments, data confidentiality becomes an unignorable issue because edge devices may be untrusted. In this paper, a secure and efficient edge computing scheme based on linear coding is proposed. Generally, linear coding can be utilized to achieve data confidentiality by encoding random blocks with original data blocks before they are distributed to unreliable edge nodes. However, the addition of a large amount of irrelevant random blocks also brings great communication overhead and high decoding complexities. In this paper, we focus on the design of secure coded edge computing using orthogonal vector to protect the information theor

关键词： Encoding Edge computing Decoding Complexity theory Computer science distributed databases Computational modeling

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Iterative Krylov Methods for Acoustic Problems on Graphics processing Unit

Iterative Krylov Methods for Acoustic Problems on Graphics P...

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13th international symposium on distributed Computing and applications to Business,Engineering & Science（DCABES 2014）

作者： Abal-Kassim Cheik Ahamed Frdric Magoulès CUDA Research Center &Applied Mathematics and Systems Laboratory Ecole Centrale Paris

This paper deals with linear algebra operations on Graphics processing Unit(GPU) with complex number arithmetic using double precision. An analysis of their uses within iterative Krylov methods is presented to solve acoustic *** experiments performed on a set of acoustic matrices arising from the modelisation of acoustic phenomena inside a car compartment are collected, and outline the performance,robustness and effectiveness of our algorithms, with a speed-up up to 28 x for dot product, 9.8x for sparse matrix-vector product and solvers.

关键词： Linear algebra Iterative Krylov methods CSR matrix GPU CUDA Acoustic Helmholtz equation parallel computing

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parallel Multi-grid Algorithm Based on Cluster Computing with Application to Transient Heat Transfer

Parallel Multi-grid Algorithm Based on Cluster Computing wit...

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2004 international symposium on distributed Computing and applications to Business, Engineering and Science

作者： Zongbo Zhu~1,Guoxun Yang~2,Chunxiao Liu~3,Jinsheng Xiao~4 1 Center of Advanced Educational Technology,Wuhan University of Technology,Hubei 430063,China 2 School of Computer Science and Technology,Wuhan University of Technology,Hubei 430063,China 3 School of Energy and Power Engineering,Wuhan University of Technology,Hubei 430063,China 4 State Key Laboratory of Advanced Technology for Materials Synthesis and processing, Wuhan University of Technology,Hubei 430070,China

The partial differential equations are often used in science and engineering *** solutions cannot be got analytical,so the numerical methods are often used to get approximate *** achieve high precision,more computing time is *** the long time in practical applications is not often allowed,so the precision of final results has to be *** on cluster system,this paper studies the parallel multi-grid method and its application in the numerical analysis of heat *** results from the sample show that the method not only can expand the size of solved problems efficiently,but also can gain excellent parallel efficiency;therefore it is a method suitable for network parallel environment based on cluster system.

关键词： parallel algorithm multi-grid algorithm heat transfer heat conduction domain decomposition methods cluster computing

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The distributed Object-Oriented Technology In Undergraduate Education of Computer Science

The Distributed Object-Oriented Technology In Undergraduate ...

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2002 international symposium on distributed Computing and applications for Business Engineering and Science

作者： Diao Cheng_Jia Information and Technology College, Nankai University Tianjin 300071, China

Based on UML, the technology of the object-oriented analysis (OOA) and the technology of object-oriented design(OOD) have been characterized by the generalization, visualization, the rapid development of the software and the easy maintenance, so that the object-oriented technology has become the popular methods in developing the large software project. However, the undergraduate education of computer science in the domestic universities only covers the studies of the object-oriented programming languages (Such as C++ or Java). In the course of software engineering, the object-oriented methods are taught as a part of the course and introduced shallowly. In the phase of graduate education, the system training is conducted. However, the distributed object-oriented technology is not taught yet. Obviously, there is a contradiction between the current situation mentioned above and the requirement to the large number of the qualified project analysts and designers, and those, who have grasped the OOA and OOD, are wanted urgently in the market. In this paper, the OOA & OOD training are discussed and some suggestions & proposals about the necessity and feasibility are also put forward.

关键词： distributed, parallel processing, the object-oriented technology, education on computer

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PIV and WPIV: Performance Index For Heterogeneous Systems Evaluation

PIV and WPIV: Performance Index For Heterogeneous Systems Ev...

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IEEE international symposium on Industrial Electronics (ISIE)

作者： Kalinka R. L. J. C. Branco Marcos Jose Santana Regina Helena Carlucci Santana Sarita Mazzini Bruschi UNIVEM University Eurípides Soares da Rocha of Marília Sao Paulo Brazil Department Computer and Mathematics Science Department Computer and Mathematics ScienceDepartment Computer and Mathematics Science ICMC-University of Sao Paulo Sao Paulo Brazil Dept. Computer and Mathematics Science ICMC - University of São Paulo P.O. Box 668 13560-970 São Carlos - SP - Brazil. rcs@icmc.usp.br

This article presents two new performance indices (PIV - performance index vector and WPIV - weighted performance index vector), to evaluate heterogeneous computing systems, based on a Euclidian metric. Aiming to maximize the use of the machines, the proposed indices are a combination of several usual indices and the results of their evaluation through a simulator show an appropriate behavior for different kinds of applications

关键词： Performance analysis Processor scheduling distributed computing parallel processing Mathematics Computer science Costs Protocols System performance Filling

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CLASSIFICATION OF LAND COVER BASED ON DEEP BELIEF NETWORKS USING POLARIMETRIC RADARSAT-2 DATA

CLASSIFICATION OF LAND COVER BASED ON DEEP BELIEF NETWORKS U...

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IEEE international Geoscience and Remote Sensing symposium

作者： Qi Lv Yong Dou Xin Niu Jiaqing Xu Baoliang Li National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology

ISBN: (纸本)9781479953141

Urban land use and land cover (LULC) classification is one of the core applications in Geographic Information System (GIS). In this paper, a novel classification approach based on Deep Belief Network (DBN) for detailed urban mapping is proposed. Deep Belief Network (DBN) is a widely investigated and deployed deep learning model. By applying the DBN model, effective spatio-temporal mapping features can be automatically extracted to improve the classification performance. Six-date RADARSAT-2 Polarimetric SAR (PolSAR) data over the Great Toronto Area were used for evaluation. Experimental results showed that the proposed method can outperform SVM and contextual approaches using adaptive MRF.

关键词： Land cover classification Deep learning Restricted Boltzmann Machines (RBMs) Deep Belief Network (DBN) PolSAR

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Power Combination Network for Image Classification on Small Samples with Data Loss

Power Combination Network for Image Classification on Small ...

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IEEE international Conference on Big Data and Cloud Computing (BdCloud)

作者： Kexin Song Fenglei Yang Zhuochen Sun School of Computer Engineering and Science Shanghai University Shanghai China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Neural networks with deeper convolutional layers are difficult to train. Improving information flows helps to simplify the training process and achieve the better accuracy. In this study, we propose a power combination network, which called PowNet. The PowNet uses fewer convolution layers than other networks before. We consider the flow of information in and between layers, rather than just maximizing the flow of information between layers. In each layer, we divide the feature maps into partitions, and use intra-layer power combination to learn the relationship between partitions to get the feature of each layer. We employ inter-layer power combination to learn the relationship between the features in different level and get the output. This comprehensive combination of structures allows the networks to learn more global information and optimize the propagation of gradients. Therefore, the networks using fewer convolutional layers can have better performance in unfavorable training or test environments. Furthermore, the networks can decrease the generalization errors. In the CIFAR-10 dataset, we show that networks using intra-layer and inter-layer power combinations can use fewer convolutional layers to achieve the similar classification accuracy. We separately evaluated the performance of PowNets and other networks in the original dataset, small samples training, and data loss, including training accuracy, test accuracy and error between them. It has shown that networks using power combination had more advanced performance. To verify the power combination's ability in reducing generalization errors, we also performed experiments in STL-10. The similar phenomenon was obtained.

关键词： distributed processing Big Data Cloud computing Social computing 6G mobile communication

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