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Indexed by:期刊论文

Date of Publication:2015-01-01

Journal:ICIC Express Letters

Included Journals:EI、Scopus

Volume:9

Issue:4

Page Number:1143-1151

ISSN No.:1881803X

Abstract: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.