DocumentCode :
688312
Title :
A Data Parallel Strategy for Haplotype Assembly Problem on Multi-core Computers
Author :
Xiao Chen ; Qinke Peng ; Libin Han
Author_Institution :
Syst. Eng. Inst. of Electron., Xi´an Jiaotong Univ., Xi´an, China
fYear :
2013
fDate :
13-15 Nov. 2013
Firstpage :
1437
Lastpage :
1442
Abstract :
Haplotype assembly problem is one of the core problems in the whole genome research, and a lot of methods have been proposed to solve this problem. However the computation time will increase greatly in the case of large-scale data for most methods. In this work, we propose a parallel strategy Par HA (Parallel Haplotype Assembly) for haplotype assembly problem based on data parallelism on multi-core computers. The SNP data were divided into several data blocks, which were processed in parallel, and the final haplotypes were constructed by fusing the results of data blocks. We have tested Par HA in terms of the reconstruction rate and the speedup, and extensive experimental results indicate that the proposed method will improve the computation efficiency significantly while achieving comparative reconstruction rate.
Keywords :
data handling; multiprocessing systems; parallel processing; shared memory systems; SNP data; data blocks; data parallel strategy; data parallelism; genome research; large-scale data; multicore computers; parallel Haplotype assembly problem; parallel strategy Par HA; reconstruction rate; shared-memory multicore CPUs; single nucleotide polymorphisms; Algorithm design and analysis; Assembly; Computers; Heuristic algorithms; Parallel algorithms; Partitioning algorithms; data parallelism; haplotype assembly; multi-core; parallel computing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (HPCC_EUC), 2013 IEEE 10th International Conference on
Conference_Location :
Zhangjiajie
Type :
conf
DOI :
10.1109/HPCC.and.EUC.2013.203
Filename :
6832085
Link To Document :
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