Efficient pairwise statistical significance estimation for local sequence alignment using GPU

Yuhong Zhang*, Sanchit Misra, Daniel Honbo, Ankit Agrawal, Wei-Keng Liao, Alok Nidhi Choudhary

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Pairwise statistical significance has been found to be quite accurate in identifying related sequences (homologs), which is a key step in numerous bioinformatics applications. However, it is computational and data intensive, particularly for a large amount of sequence data. To prevent it from becoming a performance bottleneck, we resort to Graphics Processing Units (GPUs) for accelerating the computation. In this paper, we present a GPU memory-access optimized implementation for a pairwise statistical significance estimation algorithm. By exploring the algorithm's data access characteristics, we developed a tile-based scheme that can produce a contiguous memory accesses pattern to GPU global memory and sustain a large number of threads to achieve a high GPU occupancy. Our experimental results present both single- and multi-pair statistical significance estimations. The performance evaluation was carried out on an NVIDIA Telsa C2050 GPU. We observe more than 180× end-to-end speedup over the CPU implementation on an Intel

Original languageEnglish (US)
Title of host publication2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2011
Pages226-231
Number of pages6
DOIs
StatePublished - Apr 14 2011
Event1st IEEE International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2011 - Orlando, FL, United States
Duration: Feb 3 2011Feb 5 2011

Publication series

Name2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2011

Other

Other1st IEEE International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2011
CountryUnited States
CityOrlando, FL
Period2/3/112/5/11

Keywords

  • GPU
  • Pairwise sequence alignment
  • Statistical significance

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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    Zhang, Y., Misra, S., Honbo, D., Agrawal, A., Liao, W-K., & Choudhary, A. N. (2011). Efficient pairwise statistical significance estimation for local sequence alignment using GPU. In 2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2011 (pp. 226-231). [5729885] (2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2011). https://doi.org/10.1109/ICCABS.2011.5729885