Design and optimization of DBSCAN Algorithm based on CUDA
Abstract
DBSCAN is a very classic algorithm for data clus- tering, which is widely used in many fields. However, with the data scale growing much more bigger than before, the traditional serial algorithm can not meet the performance requirement. Recently, parallel computing based on CUDA has developed very fast and has great advantage on big data. This paper summarizes the algorithms proposed before and improves the performance of the old DBSCAN algorithm by using CUDA and parallel computing. The algorithm uses shared memory as much as possible compared with other algorithms and it has very good scalability. A data set is tested on the new version of DBSCAN. Finally, we analyze the results and give a conclusion that our algorithm is approximately 97 times faster than the serial version.
Cite
@article{arxiv.1506.02226,
title = {Design and optimization of DBSCAN Algorithm based on CUDA},
author = {Bingchen Wang and Chenglong Zhang and Lei Song and Lianhe Zhao and Yu Dou and Zihao Yu},
journal= {arXiv preprint arXiv:1506.02226},
year = {2015}
}
Comments
5 pages