Research Article
Aligning Multi Sequences on GPUs
@INPROCEEDINGS{10.1007/978-3-642-36642-0_30, author={Hong Pham and Huu Nguyen and Thanh Nguyen}, title={Aligning Multi Sequences on GPUs}, proceedings={Context-Aware Systems and Applications. First International Conference, ICCASA 2012, Ho Chi Minh City, Vietnam, November 26-27, 2012, Revised Selected Papers}, proceedings_a={ICCASA}, year={2013}, month={2}, keywords={Multi sequence alignment Clustal CUDA GPU}, doi={10.1007/978-3-642-36642-0_30} }- Hong Pham
Huu Nguyen
Thanh Nguyen
Year: 2013
Aligning Multi Sequences on GPUs
ICCASA
Springer
DOI: 10.1007/978-3-642-36642-0_30
Abstract
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.
