Title
Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters.
Abstract
Evaluations show that our method achieves a peak overall performance up to 220 GCUPS for scanning real protein sequence databanks on a single node consisting of two Intel E5-2620 CPUs and two Intel Xeon Phi 7110P cards. It also exhibits good scalability in terms of sequence length and size, and number of compute nodes for both database scanning and multiple sequence alignment. Furthermore, the achieved performance is highly competitive in comparison to optimized Xeon Phi and GPU implementations. Our implementation is available at https://github.com/turbo0628/LSDBS-mpi .
Year
DOI
Venue
2016
10.1186/s12859-016-1128-0
BMC Bioinformatics
Keywords
Field
DocType
Dynamic programming,Multiple sequence alignment,Pairwise sequence alignment,Smith-Waterman,Xeon Phi clusters
Sequence alignment,Dynamic programming,Alignment-free sequence analysis,Parallel algorithm,Xeon Phi,Computer science,Software,Computational science,Smith–Waterman algorithm,Bioinformatics,Multiple sequence alignment
Journal
Volume
Issue
ISSN
17
S-9
1471-2105
Citations 
PageRank 
References 
7
0.44
30
Authors
6
Name
Order
Citations
PageRank
Haidong Lan1273.26
Yuandong Chan2233.90
Kai Xu35620.13
Bertil Schmidt469953.00
Shaoliang Peng517632.05
Weiguo Liu6917.15