@inproceedings{92c16d70b53f4d289c5c509746d42585,
title = "Parallel UPGMA algorithm on graphics processing units using CUDA",
abstract = "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.",
keywords = "CUDA, Distance matrix, Evolutionary tree construction, graphics processing units, Phylogenetic Tree, UPGMA",
author = "Chen, {Yu Rong} and Hung, {Che Lun} and Lin, {Yu Shiang} and Lin, {Chun Yuan} and Lee, {Tien Lin} and Lee, {Kual Zheng}",
year = "2012",
doi = "10.1109/HPCC.2012.120",
language = "English",
isbn = "9780769547497",
series = "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",
pages = "849--854",
booktitle = "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",
note = "null ; Conference date: 25-06-2012 Through 27-06-2012",
}