The Research of Parallelization of K-means Algorithm Based on CPU/GPU Heterogeneous Platform

摘要

Clustering analysis is widely used in data mining, e-commerce, graphic processing, bioinformation and text classification. Multicore computing based on CUDA and GPU is one of the new techniques of data processing, which became an active research direction of parallel computing in recent years. After the analysis and serial k-means algorithms, we propose a new compact parallel k-means algorithm which fit for GPU computing and present three main optimization method.The experiment results show that the algorithm is simple, fast and scalable for real-world data processing with comparison of existing other research.