Parallel UPGMA algorithm on graphics processing units using CUDA

Yu Rong Chen, Che Lun Hung, Yu Shiang Lin, Chun Yuan Lin*, Tien Lin Lee, Kual Zheng Lee

*此作品的通信作者

研究成果: Conference contribution同行評審

8 引文 斯高帕斯(Scopus)

摘要

The construction of phylogenetic trees is important for the computational biology, especially for the development of biological taxonomies. UPGMA is one of the most popular heuristic algorithms for constructing ultrametric trees (UT). Although the UT constructed by the UPGMA often is not a true tree unless the molecular clock assumption holds, the UT is still useful for the clocklike data. However, a fundamental problem with the previous implementations of this method is its limitation to handle large tax a sets within a reasonable time. In this paper, we present GPU-UPGMA which can provide a fast construction of very large datasets for biologists. Experimental results show that GPU-UPGMA obtains about 95 times speedup on NVIDIA Tesla C2050 GPU over the 2.13 GHz CPU implementation.

原文English
主出版物標題Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012
頁面849-854
頁數6
DOIs
出版狀態Published - 2012
事件14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012 - Liverpool, United Kingdom
持續時間: 25 6月 201227 6月 2012

出版系列

名字Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012

Conference

Conference14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012
國家/地區United Kingdom
城市Liverpool
期間25/06/1227/06/12

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