Publications
Talk · IEEE International Conference on Application of Information and Communication Technologies · October 1, 2018
Design of K-means clustering algorithm in PGAS based Mapreduce framework
Adai Shomanov, Мадина Мансурова, Aliya Nugumanova
Abstract
Clustering large volumes of data is a complicated and time-consuming task. The main goal of clustering task is to explore a given dataset and find appropriate set of cluster centers that have maximum within-cluster and minimum inter-cluster similarity.In our work we present parallel K-means clustering algorithm based on Partitioned Global Address Space implementation of Mapreduce model. The main idea of our approach is to exploit data locality of partitioned global address space model to assign threads to different cluster centers.
Parallel Computing and Optimization TechniquesCloud Computing and Resource ManagementAdvanced Clustering Algorithms ResearchK-means clusteringparallel clusteringPartitioned Global Address Space
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