Paper Info
Title
GPU acceleration of finding LPRs in DNA sequence based on SUA index
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.
Year
DOI
Venue
2014
10.1109/PCCC.2014.7017064
IPCCC
Keywords
Field
DocType
graphics processing unit,parallel bit compression technology,lpr,largest pattern repetition,biological sequence,parallel architectures,graphics processing units,gpu acceleration,cuda,parallel algorithms,biological sequence analysis,dna,sua index,bioinformatics,dna sequence,ptr,cuda acceleration,acceleration,algorithm design and analysis,sorting
Central processing unit,Memory bandwidth,CUDA,Parallel algorithm,Computer science,Parallel computing,General-purpose computing on graphics processing units,Graphics processing unit,Speedup,CUDA Pinned memory
Conference
ISSN
Citations 
PageRank 
1097-2641
0
0.34
References 
Authors
9
6
Name
Order
Citations
PageRank
Shufang Du101.01
Longjiang Guo217726.73
Chunyu Ai319516.30
Meirui Ren4217.30
Hao Qu510.69
Jinbao Li625139.56