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检索条件"主题词=Data Intensive Computing"
67 条 记 录,以下是31-40 订阅
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In-Map/In-Reduce: Concurrent Job Execution in MapReduce  13
In-Map/In-Reduce: Concurrent Job Execution in MapReduce
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13th IEEE International Conference on Trust Security and Privacy in computing and Communications (TrustCom)
作者: Idris, Muhammad Hussain, Shujaat Lee, Sungyoung Kyung Hee Univ Ubiquitous Comp Lab Coll Elect & Informat Seoul South Korea
Hadoop based MapReduce(MR) has emerged as big data processing mechanism in terms of its data intensive applications. In data intensive systems;analysis and visualizations as a result of various algorithms can lead to ... 详细信息
来源: 评论
Applying Selectively Parallel I/O Compression to Parallel Storage Systems  1
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20th European Conference on Parallel computing (Euro-Par)
作者: Filgueira, Rosa Atkinson, Malcolm Tanimura, Yusuke Kojima, Isao Univ Edinburgh Sch Informat Edinburgh EH8 9AB Midlothian Scotland AIST Informat Technol Res Inst Tsukuba Ibaraki Japan
This paper presents a new I/O technique called Selectively Parallel I/O Compression (SPIOC) for providing high-speed storage and access to data in QoS enabled parallel storage systems. SPIOC reduces the time of I/O op... 详细信息
来源: 评论
In-advance data Analytics for Reducing Time to Discovery  2
In-advance Data Analytics for Reducing Time to Discovery
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IEEE International Conference on Big data
作者: Liu, Jialin Lu, Yin Chen, Yong Texas Tech Univ Dept Comp Sci Lubbock TX 79409 USA
Scientific 2workflow involves data generation, data analysis, and knowledge discovery. As the data volume exceeds a few terabytes (TB) in a single simulation run, the data movement, which happens among data generation... 详细信息
来源: 评论
A general accelerated R package using GPU
A general accelerated R package using GPU
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IEEE International Conference on Smart City
作者: Jie Huang Bojin Zhuang Fei Su School of Information and Communication Engineering Beijing University of Posts and Telecommunications
In this paper, we present cuLib, a R package that provides an easy-to-access interface for utilizing the computing power of NVIDIA GPU. The cuLib package aims to make GPU-based parallel programming easier, flexible an... 详细信息
来源: 评论
Decreasing power consumption with energy efficient data aware strategies
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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2013年 第5期29卷 1152-1163页
作者: Vrbsky, Susan V. Galloway, Michael Carr, Robert Nori, Rahul Grubic, David Univ Alabama Dept Comp Sci Tuscaloosa AL 35487 USA
Regardless of whether data is stored in a cluster, grid, or cloud, data management is being recognized as a significant bottleneck. computing elements can be located far away from the data storage elements. The energy... 详细信息
来源: 评论
Towards building a multi-datacenter infrastructure for massive remote sensing image processing
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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2013年 第12期25卷 1798-1812页
作者: Zhang, Wanfeng Wang, Lizhe Liu, Dingsheng Song, Weijing Ma, Yan Liu, Peng Chen, Dan Chinese Acad Sci Ctr Earth Observat & Digital Earth Beijing Peoples R China China Univ Geosci Sch Comp Sci Wuhan 430074 Peoples R China Chinese Acad Sci Grad Univ Beijing Peoples R China
Earth observation applications are now facing the challenges of managing and processing massive data sets from multiple sources from large-scale distributed data centers (DCs). To solve this research problem, this pap... 详细信息
来源: 评论
Big data visual analytics for exploratory earth system simulation analysis
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COMPUTERS & GEOSCIENCES 2013年 第Dec.期61卷 71-82页
作者: Steed, Chad A. Ricciuto, Daniel M. Shipman, Galen Smith, Brian Thornton, Peter E. Wang, Dali Shi, Xiaoying Williams, Dean N. Oak Ridge Natl Lab Climate Change Sci Inst Oak Ridge TN 37831 USA Lawrence Livermore Natl Lab Livermore CA 94550 USA
Rapid increases in high performance computing are feeding the development of larger and more complex data sets in climate research, which sets the stage for so-called "big data" analysis challenges. However,... 详细信息
来源: 评论
Decentralized Edge Clouds
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IEEE INTERNET computing 2013年 第5期17卷 70-73页
作者: Chandra, Abhishek Weissman, Jon Heintz, Benjamin Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA Univ Minnesota Minneapolis MN 55455 USA
Nebula is a highly decentralized cloud that uses volunteer edge resources. Here, the authors provide insight into some of its key properties and design issues. They also describe a distributed MapReduce application sc... 详细信息
来源: 评论
Unified and Efficient HEC Storage System with a Working-Set based Reorganization Scheme
Unified and Efficient HEC Storage System with a Working-Set ...
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15th IEEE International Conference on Cluster computing (CLUSTER)
作者: Chen, Junjie Chen, Yong Texas Tech Univ Lubbock TX 79409 USA Texas Tech Univ Dept Comp Sci Lubbock TX 79409 USA
High-end computing (HEC) applications and simulations have become increasingly data intensive. The pressure on the storage system capability has substantially increased in recent years. Traditional hard disk drives (H... 详细信息
来源: 评论
Hierarchical I/O Scheduling for Collective I/O  13
Hierarchical I/O Scheduling for Collective I/O
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13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid computing (CCGrid)
作者: Liu, Jialin Chen, Yong Zhuang, Yu Texas Tech Univ Dept Comp Sci Lubbock TX 79409 USA
The non-contiguous access pattern of many scientific applications results in a large number of I/O requests, which can seriously limit the data-access performance. Collective I/O has been widely used to address this i... 详细信息
来源: 评论