By Topic

Parallel UPGMA Algorithm on Graphics Processing Units Using CUDA

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Yu-Rong Chen ; Dept. of Comput. Sci. & Inf. Eng., Chang Gung Univ., Taoyuan, Taiwan ; Che Lun Hung ; Yu-Shiang Lin ; Chun-Yuan Lin
more authors

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.

Published in:

High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems (HPCC-ICESS), 2012 IEEE 14th International Conference on

Date of Conference:

25-27 June 2012