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论文类型：期刊论文

发表时间：2015-01-01

发表刊物：ICIC Express Letters

收录刊物：EI、Scopus

卷号：9

期号：4

页面范围：1143-1151

ISSN号：1881803X

摘要：Collaborative filtering algorithm is the most widely used algorithm in personalized recommendation field. However, with the advent of big data era, it will be very time-consuming when the recommendation system becomes large-scale. Currently, the main method to improve the efficiency is using distributed cluster, but it may not be accessible to most researchers due to its high cost. This paper proposes a multi-GPU (Graphics Processing Unit) based parallel collaborative filtering algorithm to improve the efficiency and scalability. Experiment result shows that multi-GPU can significantly improve the running speed and the larger scale the problem is, the higher the speedup is, which provides a feasible solution to save cost for SMEs (Small and Medium-sized Enterprises). ?, 2015 ICIC international.