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企业轻量化大数据架构研究 被引量:1
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作者 李军 《科技资讯》 2023年第15期62-65,共4页
对于很多中小型的大数据项目,应用MySQL等关系型数据库无法实现大数据的存储与计算,应用传统Hadoop大数据生态又太重,比较耗费人力、财力、服务器等资源。该文研究企业轻量化大数据架构的一种落地方案,并分析其应用场景。该文研究的轻... 对于很多中小型的大数据项目,应用MySQL等关系型数据库无法实现大数据的存储与计算,应用传统Hadoop大数据生态又太重,比较耗费人力、财力、服务器等资源。该文研究企业轻量化大数据架构的一种落地方案,并分析其应用场景。该文研究的轻量化大数据架主要针对企业应用中绝大多数结构化和半结构化大数据分析,数据量规模在1TB到10PB之间。轻量化架构采用MPP数据库(Doris)作为底层存储和计算引擎,Kafka作为数据接入缓冲通道,开发一体化轻量管理组件实现大数据开发中常用的任务调度、表管理、SQL开发、数据接入等功能。 展开更多
关键词 轻量化大数据架构 MPP数据 数据任务调度 数据接入
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A Dynamic Load Balancing Method of Cloud-Center Based on SDN 被引量:6
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作者 WANG Yong TAO Xiaoling +1 位作者 HE Qian KUANG Yuwen 《China Communications》 SCIE CSCD 2016年第2期130-137,共8页
In order to balancing based on data achieve dynamic load flow level, in this paper, we apply SDN technology to the cloud data center, and propose a dynamic load balancing method of cloud center based on SDN. The appro... In order to balancing based on data achieve dynamic load flow level, in this paper, we apply SDN technology to the cloud data center, and propose a dynamic load balancing method of cloud center based on SDN. The approach of using the SDN technology in the current task scheduling flexibility, accomplish real-time monitoring of the service node flow and load condition by the OpenFlow protocol. When the load of system is imbalanced, the controller can allocate globally network resources. What's more, by using dynamic correction, the load of the system is not obvious tilt in the long run. The results of simulation show that this approach can realize and ensure that the load will not tilt over a long period of time, and improve the system throughput. 展开更多
关键词 SDN cloud computing data center dynamic load balancing
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Delay-Differentiated Scheduling in Optical Packet Switches for Cloud Data Centers 被引量:2
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作者 LI Yaofang XIAO Jie +5 位作者 WU Bin WEN Hong YU Hongfang YANG Shu XIN Shanshan GUO Jianing 《China Communications》 SCIE CSCD 2015年第8期22-32,共11页
We consider differentiated timecritical task scheduling in a N×N input queued optical packet s w itch to ens ure 100% throughput and meet different delay requirements among various modules of data center. Existin... We consider differentiated timecritical task scheduling in a N×N input queued optical packet s w itch to ens ure 100% throughput and meet different delay requirements among various modules of data center. Existing schemes either consider slot-by-slot scheduling with queue depth serving as the delay metric or assume that each input-output connection has the same delay bound in the batch scheduling mode. The former scheme neglects the effect of reconfiguration overhead, which may result in crippled system performance, while the latter cannot satisfy users' differentiated Quality of Service(Qo S) requirements. To make up these deficiencies, we propose a new batch scheduling scheme to meet the various portto-port delay requirements in a best-effort manner. Moreover, a speedup is considered to compensate for both the reconfiguration overhead and the unavoidable slots wastage in the switch fabric. With traffic matrix and delay constraint matrix given, this paper proposes two heuristic algorithms Stringent Delay First(SDF) and m-order SDF(m-SDF) to realize the 100% packet switching, while maximizing the delay constraints satisfaction ratio. The performance of our scheme is verified by extensive numerical simulations. 展开更多
关键词 delay-differentiated packetscheduling optical switch data center cloudservice
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High performance computing of DGDFT for tens of thousands of atoms using millions of cores on Sunway TaihuLight 被引量:4
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作者 Wei Hu Xinming Qin +9 位作者 Qingcai Jiang Junshi Chen Hong An Weile Jia Fang Li Xin Liu Dexun Chen Fangfang Liu Yuwen Zhao Jinlong Yang 《Science Bulletin》 SCIE EI CSCD 2021年第2期111-119,M0003,共10页
High performance computing(HPC)is a powerful tool to accelerate the Kohn–Sham density functional theory(KS-DFT)calculations on modern heterogeneous supercomputers.Here,we describe a massively parallel implementation ... High performance computing(HPC)is a powerful tool to accelerate the Kohn–Sham density functional theory(KS-DFT)calculations on modern heterogeneous supercomputers.Here,we describe a massively parallel implementation of discontinuous Galerkin density functional theory(DGDFT)method on the Sunway Taihu Light supercomputer.The DGDFT method uses the adaptive local basis(ALB)functions generated on-the-fly during the self-consistent field(SCF)iteration to solve the KS equations with high precision comparable to plane-wave basis set.In particular,the DGDFT method adopts a two-level parallelization strategy that deals with various types of data distribution,task scheduling,and data communication schemes,and combines with the master–slave multi-thread heterogeneous parallelism of SW26010 processor,resulting in large-scale HPC KS-DFT calculations on the Sunway Taihu Light supercomputer.We show that the DGDFT method can scale up to 8,519,680 processing cores(131,072 core groups)on the Sunway Taihu Light supercomputer for studying the electronic structures of twodimensional(2 D)metallic graphene systems that contain tens of thousands of carbon atoms. 展开更多
关键词 Density functional theory Tens of thousands of atoms High performance computing Sunway TaihuLight
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