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Massively Parallel and Dynamic Algorithms for Minimum Size Clustering [article]

Alessandro Epasto, Mohammad Mahdian, Vahab Mirrokni, Peilin Zhong
2021 arXiv   pre-print
Also previous dynamic and parallel algorithms do not achieve desirable complexity. We propose algorithms both in the Massively Parallel Computation (MPC) model and in the dynamic setting.  ...  In this paper, we study the r-gather problem, a natural formulation of minimum-size clustering in metric spaces.  ...  For such applications, developing a dynamic and parallel algorithms for min-size clustering is very important. We will elaborate on this application as our main motivating example.  ... 
arXiv:2106.02685v1 fatcat:ei62ajztrjcgzm2cbnkle7pyh4

PARALLEL SPATIOTEMPORAL SPECTRAL CLUSTERING WITH MASSIVE TRAJECTORY DATA

Y. Z. Gu, K. Qin, Y. X. Chen, M. X. Yue, T. Guo
2017 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
This paper presents a parallel spatiotemporal spectral clustering based on multiple acceleration solutions to make the algorithm more effective and efficient, the performance is proved due to the experiment  ...  Massive trajectory data contains wealth useful information and knowledge.  ...  Tabel4: Runtime and speedup comparison on the whole parallel algorithm for different size of dataset. Figure13. Speedup comparison on the whole parallel algorithm for different size of dataset.  ... 
doi:10.5194/isprs-archives-xlii-2-w7-1173-2017 fatcat:hd7paunfdjb6rfhvvtv4nzpnly

A fine grained parallel fuzzy segmentation algorithm on reconfigurable mesh computer

M. Youssfi, O. Bouattane, M. O. Bensalah
2015 Advanced Studies in Theoretical Physics  
In this paper, we propose a fast parallel algorithm for data classification, and its application for Magnetic Resonance Images (MRI) segmentation.  ...  The use of the massively parallel architecture in the classification domain and particularly for the fuzzy classification is introduced to improve the complexities of the corresponding algorithms.  ...  In this paper, we propose a massively parallel algorithm for fuzzy classification (fuzzy c-means) and its application to the MRI cerebral images.  ... 
doi:10.12988/astp.2015.5111 fatcat:voqsky6qwrbzhhtrejo3ufkru4

Report: GPU Based Massive Parallel Kawasaki Kinetics In Monte Carlo Modelling of Lipid Microdomains [article]

M. Lis, L. Pintal
2013 arXiv   pre-print
This paper introduces novel method of simulation of lipid biomembranes based on Metropolis Hastings algorithm and Graphic Processing Unit computational power.  ...  Extensive study of algorithm correctness is provided. Analysis of simulation results and results obtained with classical simulation methodologies are presented.  ...  Cluster Analysis Average cluster size is the time function of size of the system for fixed omega and lipid composition.  ... 
arXiv:1309.4349v1 fatcat:hdtnfimsajghpbqvecr6763kpy

Scalable Visual Analytics of Massive Textual Datasets

M. Krishnan, S. Bohn, W. Cowley, V. Crow, J. Nieplocha
2007 2007 IEEE International Parallel and Distributed Processing Symposium  
By developing a parallel implementation of the text processing engine, we enabled visual analytics tools to exploit cluster architectures and handle massive datasets.  ...  The paper describes key elements of our parallelization approach and demonstrates virtually linear scaling when processing multi-gigabyte data sets such as Pubmed.  ...  Speed-up of TREC dataset for 3 problem sizes on the Linux cluster (Left). b. Percentage of time spent on each component in the algorithm for 1 GB dataset size (Right). .  ... 
doi:10.1109/ipdps.2007.370232 dblp:conf/ipps/KrishnanBCCN07 fatcat:tkcnjcravza5fm4r2awbn3wcqi

A parallel algorithm for minimum cost path computation on polymorphic processor array [chapter]

P. Baglietto, M. Maersca, M. Migliardi
1998 Lecture Notes in Computer Science  
This paper describes a new parallel algorithm for Minimum Cost Path computation on the Polymorphic Processor Array, a massively parallel architecture based on a reconfigurable mesh interconnection network  ...  The proposed algorithm has been implemented using the Polymorphic Parallel C language and has been validated through simulation.  ...  Introduction This paper describes a parallel algorithm for the computation of the Minimum Cost Path (MCP) on the Polymorphic Processor Array (PPA), a massively parallel architecture based on a reconfigurable  ... 
doi:10.1007/3-540-64359-1_666 fatcat:g2entcrfrbg2zg3jg7jfctdxti

A Parallel Task scheduling Algorithm Based on Fuzzy Clustering in Cloud Computing Environment

Qian Zhang, Hong Liang, Yongshan Xing
2014 International Journal of Machine Learning and Computing  
Index Terms-Cloud computing, parallel scheduling, fuzzy clustering, task and resource hybrid clustering, Bayesian classification algorithm.  ...  degree of task and resource nodes and narrows task scheduling scale and, narrows task scheduling scale and at the same time lays the foundation for dynamic acheduling tasks.  ...  In fuzzy clustering algorithm [4] , the correlation coefficient between elements in fuzzy matrix usually includes angle cosine method, maximum and minimum method, arithmetic average minimum method and  ... 
doi:10.7763/ijmlc.2014.v4.451 fatcat:hcncngc3uvesjip2duato3unju

Parallel K-Medoids++ Spatial Clustering Algorithm Based on MapReduce [article]

Xia Yue, Wang Man, Jun Yue, Guangcao Liu
2016 arXiv   pre-print
In order to improve the efficiency of spatial clustering for large scale data, many researchers proposed several efficient clustering algorithms in parallel.  ...  In this paper, a new K-Medoids++ spatial clustering algorithm based on MapReduce for clustering massive spatial data is proposed.  ...  MapReduce is a parallel programming architecture for processing massive dataset. Google and Apache Hadoop both provide MapReduce framework with dynamic support and fault tolerance 7 .  ... 
arXiv:1608.06861v1 fatcat:qa7bh2fuhzfqbntp3ogdqfec5u

Parallelized event chain algorithm for dense hard sphere and polymer systems

Tobias A. Kampmann, Horst-Holger Boltz, Jan Kierfeld
2015 Journal of Computational Physics  
We combine parallelization and cluster Monte Carlo for hard sphere systems and present a parallelized event chain algorithm for the hard disk system in two dimensions.  ...  Because of the cluster nature of event chain moves massive parallelization will not be optimal.  ...  Such algorithms can also be massively parallelized for GPUs. For cluster algorithms the suitable parallelization strategy is less clear.  ... 
doi:10.1016/j.jcp.2014.10.059 fatcat:z4dlsil4gfggzo42k5itdlfeny

DELAUNAY TRIANGULATION PARALLEL CONSTRUCTION METHOD AND ITS APPLICATION IN MAP GENERALIZATION

J. Shen, L. Guo, L. Qi, W. Zhu
2012 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
But for massive data processing, current D-TIN algorithm is still not efficient enough to meet the requirements of map generalization.  ...  We tested the speed-up of the D-TIN parallel algorithm using different type of point sets and the results of the experiments shows that the method of dynamic strips partitioning can help to get high and  ...  Naijie Gu and the others of network computing and advanced algorithm laboratory of USTC (university of science and technology of China) for their help and discussion when we visited the laboratory.  ... 
doi:10.5194/isprsarchives-xxxix-b2-23-2012 fatcat:dbml3lxfj5duhhykpbnqriq35u

Mining Massive-Scale Spatiotemporal Trajectories in Parallel: A Survey [chapter]

Pengtao Huang, Bo Yuan
2015 Lecture Notes in Computer Science  
In this paper, we present a comprehensive survey of the state-of-the-art techniques for mining massive-scale spatiotemporal trajectory data based on parallel computing platforms such as Graphics Processing  ...  This survey covers essential topics including trajectory indexing and query, clustering, join, classification, pattern mining and applications.  ...  [28] proposed a parallel sequential pattern mining (plute) algorithm for massive trajectory data, which includes three essential techniques: prefix projection, data parallel formulation and task parallel  ... 
doi:10.1007/978-3-319-25660-3_4 fatcat:qdkslwlgjzesdfnzvkbrpsgmti

Cloud Computing Environments Parallel Data Mining Policy Research

Wenwu Lian, Xiaoshu Zhu, Jie Zhang, Shangfang Li
2015 International Journal of Grid and Distributed Computing  
This paper presents a cloud computing environment suitable for partitioning the data set allocation method and data sets; introduces improved Apriori algorithm based on its calculation of two parallel  ...  previously used researcher science and algorithms .  ...  Acknowledgements The work in this paper has been supported by funding from Natural Science Foundation of Guangxi (No.2013GXNSFAA019337), from Key Project of Guangxi Education Department (No.2013ZD055), and  ... 
doi:10.14257/ijgdc.2015.8.4.13 fatcat:razzyb4qv5fhdfmlhm2zh5ynnq

A PARALLEL CLUSTER LABELING METHOD FOR MONTE CARLO DYNAMICS

MIKE FLANIGAN, PABLO TAMAYO
1992 International Journal of Modern Physics C  
We present an algorithm for cluster dynamics to efficiently simulate large systems on MIMD parallel computers with large numbers of processors.  ...  The algorithm has been used to simulate large 2d Ising systems (up to 27808 X 27808 sites) with Swendsen-Wang dynamics.  ...  Apostolakis and E. Marinari, for interesting discussions about cluster methods and their applications.  ... 
doi:10.1142/s0129183192000853 fatcat:3lv6vjarfng4plysup7s7azkpa

Mining Association Rules on Grid Platforms [chapter]

Raja Tlili, Yahya Slimani
2012 Lecture Notes in Computer Science  
In this paper we propose a dynamic load balancing strategy to enhance the performance of parallel association rule mining algorithms in the context of a Grid computing environment.  ...  This strategy is built upon a distributed model which necessitates small overheads in the communication costs for load updates and for both data and work transfers.  ...  Parallelism is expected to relieve these algorithms from the sequential bottleneck, providing the ability to scale the massive datasets, and improving the response time.  ... 
doi:10.1007/978-3-642-29737-3_23 fatcat:m5sbvwpr6zcnxaq47hi5emjjje

A Parallel GPU-Based Approach to Clustering Very Fast Data Streams

Pengtao Huang, Xiu Li, Bo Yuan
2015 Proceedings of the 24th ACM International on Conference on Information and Knowledge Management - CIKM '15  
Driven by the ever increasing volume, velocity and variety of data, more efficient algorithms for clustering large-scale complex data streams are needed.  ...  In this paper, we present a parallel algorithm called PaStream, which is based on advanced Graphics Processing Unit (GPU) and follows the online-offline framework of CluStream.  ...  Unlike traditional static data stored in databases or data warehouses, data stream is a dynamic, continuous, massive, unbounded and rapid sequence of data.  ... 
doi:10.1145/2806416.2806545 dblp:conf/cikm/HuangLY15 fatcat:mrcsqqlwnvdnjpy3ax6fgoc7la
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