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An Implementation of GPU-Based Parallel Optimization for an Extended Uncertain Data Query Algorithm

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3 Author(s)
Chen Ningjiang ; Coll. of Comput., Electron., & Inf., Guangxi Univ., Nanning, China ; Yu Minmin ; Hu Dandan

To deal with users' diversified query requirements on uncertain data, an uncertain data query semantic for requirement extension named RU-Topk is introduced. In the high-load application environment, the top-k query algorithm's response time may be long. In order to satisfy performance requirements, with the consideration of the algorithm's features, the design and implementation of GPU-based RU-Topk algorithm as well as a batch scheduling strategy are presented. Finally, the experimental results on GPU platform show that they can obtain optimized performance.

Published in:

Parallel Architectures, Algorithms and Programming (PAAP), 2011 Fourth International Symposium on

Date of Conference:

9-11 Dec. 2011

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