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Research on key technologies of edge cache in virtual data space across WAN

Frontiers of computer science 2023年第1期17卷 15-34页

作者： Jiantong HUO Yaowen XU Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China College of Software Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China College of Computer Science and Technology Zhejiang UniversityHangZhou 310013China

The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputing Center in Guangzhou, National Supercomputing Center in Jinan, National Supercomputing Center in Changsha, Shanghai Supercomputing Center, and computer Network Information Center in Chinese Academy of sciences) into a storage system that spans the wide area network (WAN), which realizes the unified management of global storage resources in China. At present, the GVDS has been successfully deployed in the China National Grid environment. However, when accessing and sharing remote data in the WAN, the GVDS will cause redundant transmission of data and waste a lot of network bandwidth resources. In this paper, we propose an edge cache system as a supplementary system of the GVDS to improve the performance of upper-level applications accessing and sharing remote data. Specifically, we first designs the architecture of the edge cache system, and then study the key technologies of this architecture: the edge cache index mechanism based on double-layer hashing, the edge cache replacement strategy based on the GDSF algorithm, the request routing based on consistent hashing method, and the cluster member maintenance method based on the SWIM protocol. The experimental results show that the edge cache system has successfully implemented the relevant operation functions (read, write, deletion, modification, etc.) and is compatible with the POSIX interface in terms of function. Further, it can greatly reduce the amount of data transmission and increase the data access bandwidth when the accessed file is located at the edge cache system in terms of performance, i.e., its performance is close to the performance of the network file system in the local area network (LAN).

关键词： virtual data space system wide area network edge cache redundant data transmission

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Study and Analysis of Hadoop Cluster Optimization based on configuration properties

Study and Analysis of Hadoop Cluster Optimization based on c...

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International Conference on Innovations in Power and Advanced computing Technologies

作者： Motahar Reza Badrinath Tripathy Harsh Ranjan G. Anant Kumar High Performance Computing Lab School of Computer Science and Engineering National Institute of Science and Technology Berhampur-761008 India

ISBN: (纸本)9781509056835

Hadoop framework consists of multiple components. One set of configuration parameters may not be suitable for all types of applications. Hence, for optimum performance, each framework parameter needs to be carefully chosen and adjusted. This paper highlights some of the important configuration properties related to Block size, memory allocation, CPU allocation, Number of MapReduce jobs, Job scheduling and JVM which should be tuned for improved Hadoop application performance. The result of some Benchmark problems are analyzed.

关键词： Hadoop framework JVM CPU Allocation Benchmark

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SOCA-DOM:A Mobile System-on-Chip Array System for Analyzing Big Data on the Move

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Journal of computer science & Technology 2022年第6期37卷 1271-1289页

作者： Le-Le Li Jiang-Yi Liu Jian-Ping Fan Xue-Hai Qian Kai Hwang Yeh-Ching Chung Zhi-Bin Yu Center for Heterogeneous and Intelligent Computing Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518055China School of Science and Engineering The Chinese University of Hong KongShenzhenShenzhen 518172China Center for High Performance Computing Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Shenzhen 518055China Ming Hsieh Department of Electrical and Computer Engineering University of Southern CaliforniaLos Angeles CA 90089-0001U.S.A. Department of Computer Science University of Southern CaliforniaLos AngelesCA 90089-0001U.S.A. School of Data and Science The Chinese University of Hong KongShenzhenShenzhen 518172China

Recently,analyzing big data on the move is *** requires that the hardware resource should be low volume,low power,light in weight,high-performance,and highly scalable whereas the management software should be flexible and consume little hardware *** meet these requirements,we present a system named SOCA-DOM that encompasses a mobile system-on-chip array architecture and a two-tier“software-defined”resource manager named ***,we design an Ethernet communication board to support an array of mobile ***,we propose a two-tier software architecture for Chameleon to make it ***,we devise data,configuration,and control planes for Chameleon to make it“software-defined”and in turn consume hardware resources on ***,we design an accurate synthetic metric that represents the computational power of a computing *** employ 12 Apache Spark benchmarks to evaluate ***,SOCA-DOM consumes up to 9.4x less CPU resources and 13.5x less memory than Mesos which is an existing resource *** addition,we show that a 16-node SOCA-DOM consumes up to 4x less energy than two standard Xeon *** on the results,we conclude that an array architecture with fine-grained hardware resources and a software-defined resource manager works well for analyzing big data on the move.

关键词： edge computing mobile architecture resource management big data analytics software-defined systems

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Effective Deep Learning Data Augmentation Techniques for Diabetic Retinopathy Classification

Effective Deep Learning Data Augmentation Techniques for Dia...

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2022 International Conference on Machine Learning and Data engineering, ICMLDE 2022

作者： Patil, Mahesh S Chickerur, Satyadhyan Abhimalya, C. Naik, Anishma Kumari, Nidhi Maurya, Shashank School of Computer Science and Engineering K L e Technological University Karnataka Hubballi580031 India Center for High Performance Computing K L e Technological University Karnataka Hubballi580031 India

Diabetic retinopathy(DR) is an eye disorder that affects 80-85% of diabetic patients, and there is a need to detect it in earlier stages to take precautions. Currently, testing for DR is a time-consuming task and requires qualified human resources. Automating DR detection is time-saving and cost-effective, benefiting both doctors and patients. The proposed work automates the DR image detection using deep learning(DL) by using transfer learning. The proposed work provides better results with multi-class classification and generalization than the previous works. i.e a ResNet-50 DL model is trained with the APTOS dataset and tested using the EyePACS dataset. The low accuracy in multi-class classification and data imbalance problems are overcome by using appropriate image pre-processing and augmentation techniques, which have been found by conducting several experiments. Further, the performance of the DL model is enhanced using Test Time Augmentation(TTA). Finally, the authors are able to achieve a multi-class accuracy of 97.87% and Quadratic weighted kappa(QWK) score of 0.985. © 2023 The Authors. Published by Elsevier B.V.

关键词： Classification (of information)

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Study of Data and Model parallelism in Distributed Deep learning for Diabetic retinopathy classification

Study of Data and Model parallelism in Distributed Deep lear...

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2022 International Conference on Machine Learning and Data engineering, ICMLDE 2022

作者： Patil, Mahesh S. Chickerur, Satyadhyan School of Computer Science and Engineering K L e Technological University Karnataka Hubballi580031 India Center for High Performance Computing K L e Technological University Karnataka Hubballi580031 India

Distributed deep learning(DDL) is an area of research in Artificial intelligence (AI), where the training time of deep learning(DL) models can be drastically reduced by using multiple accelerators. Most of the previous research works use the data parallelism strategy of DDL and report its performance. But, other parallelism strategies in DDL need to be explored and report its performance modeling for particular applications and software-hardware stacks. Such works can help other researchers make better decisions in designing an efficient DDL algorithm. This work presents a comparative study of data parallelism(DP) and model parallelism(MP) for DDL. The diabetic retinopathy(DR) image classification is used as a case study, and DDL algorithms are implemented using Mesh-Tensor Flow on NVidia's DGX-1. As indicated by the results, the MP strategy provides faster convergence and higher validation accuracy of 62.13% compared to DP strategies validation accuracy of 55.72%. Also, the MP strategy surpasses the DP's highest accuracy in lesser epochs with a speed-up of 1.38X in terms of time duration. Overall, this unique study provides a performance comparison between DP and MP strategies of DDL algorithms being applied for a particular application, dataset, and software-hardware stack. © 2023 The Authors. Published by Elsevier B.V.

关键词： Deep learning

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Human-cyber-physical systems:concepts,challenges,and research opportunities

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Frontiers of Information Technology & Electronic engineering 2020年第11期21卷 1535-1553页

作者： Zhiming LIU Ji WANG RISE-Centre for Research and Innovation in Software Engineering School of Computer and Information ScienceSouthwest UniversityChongqing 400715China State Key Laboratory for High Performance Computing School of ComputerNational University of Defense TechnologyChangsha 410073China

In this perspective article,we first recall the historic background of human-cyber-physical systems(HCPSs),and then introduce and clarify important *** discuss the key challenges in establishing the scientific foundation from a system engineering point of view,including(1)complex heterogeneity,(2)lack of appropriate abstractions,(3)dynamic black-box integration of heterogeneous systems,(4)complex requirements for functionalities,performance,and quality of services,and(5)design,implementation,and maintenance of HCPS to meet *** we propose four research directions to tackle the challenges,including(1)abstractions and computational theory of HCPS,(2)theories and methods of HCPS architecture modelling,(3)specification and verification of model properties,and(4)software-defined *** article also serves as the editorial of this special section on cyber-physical systems and summarises the four articles included in this special section.

关键词： Abstractions Architecture modelling Evolution Software-defined technology

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Pipeline Parallelism in Distributed Deep Learning for Diabetic Retinopathy Classification 4th

Pipeline Parallelism in Distributed Deep Learning for Diabet...

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4th International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2022

作者： Patil, Shashank Anand Patil, Mahesh S. Giraddi, Shantala Chickerur, Satyadhyan Boormane, Vinayak M. Gamanagatti, Ganesh School of Computer Science and Engineering K L e Technological University Karnataka Hubballi580031 India Center for High Performance Computing K L e Technological University Karnataka Hubballi580031 India

Deep learning (DL) has been used widely and successfully in a variety of industries. It is challenging for researchers to carry out their experiments to find the optimal learning model because training the deep learning model is a time-consuming operation. Distributed deep learning offers a technique for rapid training of DL models (DDL). It is difficult to create and implement DDL, nevertheless, so it is important to report on the performance analysis of different DDL algorithms for the benefit of the research community. The authors of this proposed study use two GPUs to design, construct, and analyse a pipeline parallelism in DDL and then present an analysis of its performance. As a case study for DDL implementation, the authors employ diabetic retinopathy classification. 0.834 is obtained as the validation F1 score. The performance of DDL is reported and examined by the authors, and it is demonstrated to improve training effectiveness in terms of both time and speed. © 2023 The Authors. Published by Elsevier B.V.

关键词： Graphics processing unit

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An Extrapolation Cascadic MultigridMethod for Elliptic Problems on Reentrant Domains

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Advances in Applied Mathematics and Mechanics 2017年第6期9卷 1347-1363页

作者： Kejia Pan Dongdong He Chuanmiao Chen School of Mathematics and Statistics Central South UniversityChangshaHunan 410083China School of Aerospace Engineering and Applied Mechanics Tongji UniversityShanghai 200092China College of Mathematics and Computer Science Key Laboratory of High Performance Computing and Stochastic Information Processing(Ministry of Education of China)Hunan Normal UniversityChangshaHunan 410081China

This paper proposes an extrapolation cascadic multigrid(EXCMG)method to solve elliptic problems in domains with reentrant *** a class ofλ-graded meshes,we derive some new extrapolation formulas to construct a high-order approximation to the finite element solution on the next finer mesh using the numerical solutions on two-level of grids(current and previous grids).Then,this high-order approximation is used as the initial guess to reduce computational cost of the conjugate gradient *** application of this idea results in the EXCMG method proposed in this ***,numerical results for a crack problem and an L-shaped problem are presented to verify the efficiency and effectiveness of the proposed EXCMG method.

关键词： Richardson extrapolation Cascadicmultigrid gradedmesh elliptic problems corner singularity

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Terrain polygon decomposition, with application to layered manufacturing 8th

Terrain polygon decomposition, with application to layered m...

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8th Annual International Conference on computing and Combinatorics, COCOON 2002

作者： Ilinkin, Ivaylo Janardan, Ravi Smid, Michiel Dept. of Computer Science & Engineering and Army High Performance Computing Research Center University of Minnesota MinneapolisMN55455 United States School of Computer Science Carleton University OttawaK1S 5B6 Canada

ISBN: (纸本)354043996X

Efficient algorithms are given for decomposing a simple polygon into two special polygons, each with the property that every boundary and interior point can be connected to a single edge by a perpendicular line segment interior to the polygon. This allows efficient construction of certain classes of 3D parts via Layered Manufacturing. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Geometry

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A powder-scale multiphysics framework for powder bed fusion of fiber-reinforced polymer composites

Advanced Powder Materials

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Advanced Powder Materials 2024年第4期3卷 47-56页

作者： Pengfei Tan Meixin Zhou Chao Tang Kun Zhou HP-NTU Digital Manufacturing Corporate Lab School of Mechanical and Aerospace EngineeringNanyang Technological UniversitySingapore 639798Singapore Singapore Centre for 3D Printing School of Mechanical and Aerospace EngineeringNanyang Technological UniversitySingapore 639798Singapore Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A*STAR)Singapore 138632Singapore

Additive manufacturing of fiber-reinforced polymer composites has garnered great interest due to its potential in fabricating functional products with lightweight characteristics and unique material ***,the major concern in polymer composites remains the presence of pore defects,as a thorough understanding of pore formation is *** this study,a powder-scale multiphysics framework has been developed to simulate the printing process of fiber-reinforced polymer composites in powder bed fusion additive *** numerical framework involves various multiphysics phenomena such as particle flow dynamics of fiber-reinforced polymer composite powder,infrared laser–particle interaction,heat transfer,and multiphase fluid flow *** melt depths of one-layer glass fiber–reinforced polyamide 12 composite parts fabricated by selective laser sintering are measured to validate modelling *** numerical framework is employed to conduct an in-depth investigation of pore formation mechanisms within printed *** simulation results suggest that an increasing fiber weight fraction would lead to a lower densification rate,larger porosity,and lower pore sphericity in the composites.

关键词： Additive manufacturing Powder bed fusion Polymeric materials Multiphysics modelling Porosity

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