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Big Data Visualization Collaborative Filtering Algorithm Based on RHadoop

Lijun Cai, Xiangqing Guan, Peng Chi, Lei Chen, Jianting Luo
2015 International Journal of Distributed Sensor Networks  
While the analysis tools of big data visualization is very rare, in this paper, we propose a new big data visualization algorithm analysis integrated model.  ...  The model integrates the processing of big data and the visualization of data as a whole. It is a good analysis tool of timely big data visualization.  ...  Acknowledgments This work is supported by the national science and technology support program of China (Grant no. 2012BAH09B02) and key science and technology project of Hunan Province (Grant no.  ... 
doi:10.1155/2015/271253 fatcat:bayboicuobg55fqczfvylk4mim

The SDAV Software Frameworks for Visualization and Analysis on Next-Generation Multi-Core and Many-Core Architectures

Christopher Sewell, Jeremy Meredith, Kenneth Moreland, Tom Peterka, Dave DeMarle, Li-ta Lo, James Ahrens, Robert Maynard, Berk Geveci
2012 2012 SC Companion: High Performance Computing, Networking Storage and Analysis  
This paper surveys the four software frameworks being developed as part of the visualization pillar of the SDAV (Scalable Data Management, Analysis, and Visualization) Institute, one of the SciDAC (Scientific  ...  These frameworks include EAVL (Extreme-scale Analysis and Visualization Library), Dax (Data Analysis at Extreme), DIY (Do It Yourself), and PISTON.  ...  ACKNOWLEDGMENT The SciDAC Institute of Scalable Data Management, Analysis, and Visualization (SDAV) is funded by the DOE Office of Science through the Office of Advanced Scientific Computing Research (  ... 
doi:10.1109/sc.companion.2012.36 dblp:conf/sc/SewellMMPDLAMG12 fatcat:qyzavpdqgbepxkt6inswr2vxsy


Steve Petruzza, Aniketh Venkat, Attila Gyulassy, Giorgio Scorzelli, Frederick Federer, Alessandra Angelucci, Valerio Pascucci, Peer-Timo Bremer
2017 SIGGRAPH Asia 2017 Symposium on Visualization on - SA '17  
CCS CONCEPTS Computing methodologies → Massively parallel algorithms; Parallel programming languages; Software and its engineering → Development frameworks and environments; Integrated and visual development  ...  environments Keywords Interactive visualization and analysis; parallel custom analysis work-flows; algorithms scalability; microscopy  ...  They are typically executed in parallel, coordinating visualization and analysis tasks for massive data.  ... 
doi:10.1145/3139295.3139299 pmid:30148289 pmcid:PMC6105268 dblp:conf/siggraph/PetruzzaVGSFAPB17 fatcat:ppcwkpk32jd65arcaw3nrnvzne

Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends

Emad A Mohammed, Behrouz H Far, Christopher Naugler
2014 BioData Mining  
MapReduce is a new parallel processing framework and Hadoop is its open-source implementation on a single computing node or on clusters.  ...  The emergence of massive datasets in a clinical setting presents both challenges and opportunities in data storage and analysis.  ...  A practical framework [66] based on MapReduce programming framework is developed to infer large gene networks, by developing and parallelizing a hybrid genetic algorithm particle swarm optimization (  ... 
doi:10.1186/1756-0381-7-22 pmid:25383096 pmcid:PMC4224309 fatcat:zpis7kklerh2vna5le2gtxc5vi

Big Data Analysis of Marketing User Intelligence Information Based on Deep Learning

Zhongqi Shen, Muhammad Muzammal
2022 Mobile Information Systems  
To solve the problem that the explosive growth of data cannot be effectively analyzed, a big data analysis and prediction system based on deep learning is proposed.  ...  Compared with the other two, the network optimized by DCNNPS is less sensitive to data growth in the scenario of a large amount of data and is more suitable for processing a large amount of data.  ...  Nowadays, deep learning has gradually developed into an important method for a large amount of data analysis and prediction.  ... 
doi:10.1155/2022/2990649 fatcat:jayhd7p4mjd3bihiqwl36g7og4

A Framework for Visual Dynamic Analysis of Ray Tracing Algorithms

Hristo Lesev, Alexander Penev
2014 Cybernetics and Information Technologies  
A novel approach is presented for recording high volume data about ray tracing rendering systems' runtime state and its subsequent dynamic analysis and interactive visualization in the algorithm computational  ...  The framework provides data logging API for instrumenting production-ready, multithreaded, distributed renderers.  ...  Our main goal is to create a modular architecture of a framework that enhances visualization and dynamic analysis of ray tracing algorithms in computer graphics domain.  ... 
doi:10.2478/cait-2014-0018 fatcat:xymzqqlchnc37apv3zsidstg44

Open source tools for large-scale neuroscience

Jeremy Freeman
2015 Current Opinion in Neurobiology  
New technologies for monitoring and manipulating the nervous system promise exciting biology but pose challenges for analysis and computation.  ...  Solutions can be found in the form of modern approaches to distributed computing, machine learning, and interactive visualization.  ...  Graphical representations inform both our understanding of data and our development of analyses; a visualization can be the best guide for how an algorithm works [40] .  ... 
doi:10.1016/j.conb.2015.04.002 pmid:25982977 fatcat:zvggfg4pczh7fnepihqgxzd3zq

Machine Learning and Cloud Computing: Survey of Distributed and SaaS Solutions [article]

Daniel Pop
2016 arXiv   pre-print
Next on the list are libraries of distributed implementations for ML algorithms, and on-premise deployments of complex systems for data analytics and data mining.  ...  Parallelization using modern parallel computing frameworks, such as MapReduce, CUDA, or Dryad gained in popularity and acceptance, resulting in new ML libraries developed on top of these frameworks.  ...  It exposes a multi-layered framework where developers may express their ML-DM algorithms as tasks.  ... 
arXiv:1603.08767v1 fatcat:vuzeggijyfbb7bmlcqdnt3xdjy

Research of the Social Media Data Analyzing Platform Based on Cloud Mining

Yi-Tang ZENG, Yu-Feng ZHANG, Sheng CAO, Li LI, Cheng-Wei ZHANG
2017 DEStech Transactions on Social Science Education and Human Science  
This research provides a feasible way of thinking and method for the mining and analysis of social media data.  ...  In this paper, the cloud mining is introduced, and the principles of cloud mining technology are explored, a logical and a physical framework of social media data analyzing platform based on cloud mining  ...  It provides premise and foundation for the deep development and utilization of big data [5] .  ... 
doi:10.12783/dtssehs/icss2016/9180 fatcat:ko6ecgtkezb2tpkrqb327cs2jy

Development and Integration of an In-Situ Framework for Flow Visualization of Large-Scale, Unsteady Phenomena

2017 Supercomputing Frontiers and Innovations  
Enabling in-situ visualization in a simulation model asks for special attention to the interface between a parallel simulation model and the data analysis part of the visualization, and to presentation  ...  We focus on the requirements for generalized grid and data structures, and for universal, scalable algorithms for volume and flow visualization of time series.  ...  This paper is distributed under the terms of the Creative Commons Attribution-Non Commercial 3.0 License which permits non-commercial use, reproduction and distribution of the work without further permission  ... 
doi:10.14529/jsfi170303 fatcat:jt5c3ourxvc3tcgkzwoyfev22e

Research Challenges for Visualization Software

Hank Childs, Berk Geveci, Will Schroeder, Jeremy Meredith, Kenneth Moreland, Christopher Sewell, Torsten Kuhlen, E. Wes Bethel
2013 Computer  
His research interests include portable data-parallel programming models for visualization and analysis, and in situ visualization and analysis within simulation codes.  ...  Beyond massive parallelism, intelligent scheduling and data reduction techniques are necessary for a visualization software framework to achieve full interactivity.  ... 
doi:10.1109/mc.2013.179 fatcat:ej2iumbowjefxnz3lbtwnb7jji

Introduction to Big Data Computing for Geospatial Applications

Zhenlong Li, Wenwu Tang, Qunying Huang, Eric Shook, Qingfeng Guan
2020 ISPRS International Journal of Geo-Information  
The convergence of big data and geospatial computing has brought challenges and opportunities to GIScience with regards to geospatial data management, processing, analysis, modeling, and visualization.  ...  the opportunities for using big data for geospatial applications.  ...  Acknowledgments: We would like to thank all authors for contributing to this special issue and the reviewers for their constructive suggestions and criticisms that significantly improved the papers in  ... 
doi:10.3390/ijgi9080487 fatcat:b5qd7ar76feydjakfbr64xknsq

Survey of MapReduce on Big Data

Mr.A.Antony Prakash, Dr. A. Aloysius
2017 International Journal Of Engineering And Computer Science  
Hadoop is an open source software project used to processing a large data sets. MapReduce is a programming model that associated implementation for parallel processing of large dataset.  ...  Big data environment is used to acquire, organize and analyze the various types of data. There is an observation about MapReduce framework. This framework generates large amount of intermediate data.  ...  MapReduce for data visualization currently performs well in two cases: memory-insensitive visualization algorithms, and inherently parallel visualization algorithms, Vo et al [24] .  ... 
doi:10.18535/ijecs/v6i3.49 fatcat:tiqxc6djjjbrtndc7qmaep3z7e

Daisy: Data analysis integrated software system for X-ray experiments [article]

Yu Hu, Ling Li, Haolai Tian, Zhibing Liu, Qiulan Huang, Yi Zhang, Hao Hu, Fazhi Qi
2021 arXiv   pre-print
Daisy (Data Analysis Integrated Software System) has been designed for the analysis and visualization of the X-ray experiments.  ...  support on-site data analysis services with fast feedback and interaction.  ...  A user-friendly integrated A B development environment and graphic user interface should be provided for end-users to integrate algorithms and set up data analysis applications.  ... 
arXiv:2103.00786v1 fatcat:gbfxhntonvbsjnwl33dqvy5s5y

Ultra-Scale Visualization: Research and Education

Kwan-Liu Ma, Robert Ross, Jian Huang, Greg Humphreys, Nelson Max, Kenneth Moreland, John D Owens, Han-Wei Shen
2007 Journal of Physics, Conference Series  
Visualization is the most intuitive means for scientists to understand data at this scale, and the most effective way to communicate their findings with others.  ...  The Institute for Ultra-Scale Visualization (IUSV), funded by the DOE SciDAC-2 program, has the mission to advance visualization technologies to enable knowledge discovery and dissemination for petascale  ...  You are all critical in our understanding of the needs of the community and provide invaluable feedback during the research and development process.  ... 
doi:10.1088/1742-6596/78/1/012088 fatcat:c6phldibwbdnxggvodgjodyoau
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