MGUPGMA: A Fast UPGMA Algorithm With Multiple Graphics Processing Units Using NCCL

A phylogenetic tree is a visual diagram of the relationship between a set of biological species. The scientists usually use it to analyze many characteristics of the species. The distance-matrix methods, such as Unweighted Pair Group Method with Arithmetic Mean and Neighbor Joining, construct a phyl...

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Bibliographic Details
Main Authors: Guan-Jie Hua, Che-Lun Hung, Chun-Yuan Lin, Fu-Che Wu, Yu-Wei Chan, Chuan Yi Tang
Format: Article
Language:English
Published: SAGE Publishing 2017-10-01
Series:Evolutionary Bioinformatics
Online Access:https://doi.org/10.1177/1176934317734220
Description
Summary:A phylogenetic tree is a visual diagram of the relationship between a set of biological species. The scientists usually use it to analyze many characteristics of the species. The distance-matrix methods, such as Unweighted Pair Group Method with Arithmetic Mean and Neighbor Joining, construct a phylogenetic tree by calculating pairwise genetic distances between taxa. These methods have the computational performance issue. Although several new methods with high-performance hardware and frameworks have been proposed, the issue still exists. In this work, a novel parallel Unweighted Pair Group Method with Arithmetic Mean approach on multiple Graphics Processing Units is proposed to construct a phylogenetic tree from extremely large set of sequences. The experimental results present that the proposed approach on a DGX-1 server with 8 NVIDIA P100 graphic cards achieves approximately 3-fold to 7-fold speedup over the implementation of Unweighted Pair Group Method with Arithmetic Mean on a modern CPU and a single GPU, respectively.
ISSN:1176-9343