DocumentCode
235162
Title
GPU acceleration of finding LPRs in DNA sequence based on SUA index
Author
Shufang Du ; Longjiang Guo ; Chunyu Ai ; Meirui Ren ; Hao Qu ; Jinbao Li
Author_Institution
Sch. of Comput. Sci. & Technol., Heilongjiang Univ., Harbin, China
fYear
2014
fDate
5-7 Dec. 2014
Firstpage
1
Lastpage
8
Abstract
The repetitions in biological sequence analysis are of great biological significance. Finding the repetitions has been a hot topic in gene projects naturally. In recent years, graphics processing unit (GPU) has been far exceeded the CPU in terms of computing capability and memory bandwidth, especially CUDA dramatically increases in computing performance by harnessing the power of the GPUs. This paper proposes efficient parallel algorithms on CUDA to accelerate finding PTRs which is redefined as LPRs based on the SUA Index. The proposed parallel algorithms have been utilized with the parallel primitives offered by Thrust library and the effective parallel bit compression technology based on division to achieve better acceleration. Optimization techniques include CUDA streams technology are also realized to reduce transmission latency. Experimental results show that the proposed parallel algorithms are faster than the benchmark with 1.6~5.4 speedup.
Keywords
DNA; bioinformatics; graphics processing units; parallel algorithms; parallel architectures; CUDA; DNA sequence; GPU acceleration; LPR; SUA index; biological sequence analysis; graphics processing unit; parallel algorithms; parallel bit compression technology; Acceleration; Algorithm design and analysis; Arrays; DNA; Graphics processing units; Parallel algorithms; Sorting; Biological Sequence; CUDA Acceleration; Largest Pattern Repetition; PTR;
fLanguage
English
Publisher
ieee
Conference_Titel
Performance Computing and Communications Conference (IPCCC), 2014 IEEE International
Conference_Location
Austin, TX
Type
conf
DOI
10.1109/PCCC.2014.7017064
Filename
7017064
Link To Document