Aligning Multi Sequences on GPUs

被引：0

作者：

Hong Phong Pham ^{[1
]}

Huu Duc Nguyen ^{[1
]}

Thanh Thuy Nguyen ^{[2
]}

机构：

[1] Hanoi Univ Sci & Technol, Dept Informat Syst, NOT Is High Performance Comp Ctr, Hanoi, Vietnam

[2] VNU Univ Engn & Technol, Dept Comp Sci, Hanoi, Vietnam

来源：

Context-Aware Systems and Applications, (ICCASA 2012) | 2013年 / 109卷

关键词：

Multi sequence alignment; Clustal; CUDA; GPU; ALIGNMENT;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Implementing Multi Sequence Alignment (MSA) problem using the method of progressive alignment is not feasible on common computing systems; it takes several hours or even days for aligning thousands of sequences if we use sequential versions of the most popular MSA algorithm - Clustal. In this paper, we present our parallel algorithm called CUDAClustal, a MSA parallel program. We have paralleled the first stage of the algorithm Clustal and achieved a significant speedup when compared to the sequential program running on a computer of Pentium 4 3.0 GHz processor. Our tests were performed on one GPU Geforce GTX 295 and they gave a great computing performance: the running time of CUDAClustal is smaller approximately 30 times than Clustal for the first stage. This shows the large benefit of GPU for solving the MSA problem and its high applicability in bioinformatics.

引用

页码：300 / 309

页数：10

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