An Implementation of GPU-Based Parallel Optimization for an Extended Uncertain Data Query Algorithm
Ningjiang Chen, Yu Minmin, Dandan Hu · 2011
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.