Issue |
ITM Web Conf.
Volume 12, 2017
The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|
|
---|---|---|
Article Number | 03046 | |
Number of page(s) | 5 | |
Section | Session 3: Computer | |
DOI | https://doi.org/10.1051/itmconf/20171203046 | |
Published online | 05 September 2017 |
GPU-Accelerated Apriori Algorithm
School of Computer Science and Engineering, Southeast University, Nanjing, China
a hjiang@seu.edu.cn
b wei1517@126.com
c zyliu278@163.com
d 756250742@qq.com
This paper propose a parallel Apriori algorithm based on GPU (GPUApriori) for frequent itemsets mining, and designs a storage structure using bit table (BIT) matrix to replace the traditional storage mode. In addition, parallel computing scheme on GPU is discussed. The experimental results show that GPUApriori algorithm can effectively improve the efficiency of frequent itemsets mining.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.