FPGA-based Smith-Waterman algorithm: Analysis and novel design

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6578 LNCS, Issue , 2011, Pages 181-192

  Yamaguchi, Yoshiki ^a   Tsoi, Hung Kuen ^b   Luk, Wayne ^b  

^a UNIVERSITY OF TSUKUBA   (Japan)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

dynamic programming; Performance comparison

Indexed keywords

ENERGY EFFICIENT; FPGA DESIGN; NOVEL DESIGN; PEAK PERFORMANCE; PERFORMANCE COMPARISON; POWER EFFICIENCY; PROCESSING ELEMENTS; SMITH-WATERMAN ALGORITHM; PAPER ANALYSIS;

ALGORITHMS; DESIGN; PROGRAM PROCESSORS; COST FUNCTIONS; DYNAMIC PROGRAMMING; ENERGY EFFICIENCY; FIELD PROGRAMMABLE GATE ARRAYS (FPGA); RECONFIGURABLE ARCHITECTURES;

DYNAMIC PROGRAMMING; INTEGRATED CIRCUIT DESIGN;

EID: 79953175270     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-19475-7_20     Document Type: Conference Paper

References (18)

1. Altschul, S.F., Gish,W., Miller, W., Myers, E.W., Lipman, D.J.: Basic Local Alignment Search Tool. Molecular Biology 215(3), 403-410 (1990)
2. Pearson, W.R.: Comparison of methods for searching protein sequence databases. Profein Science 4(6), 1145-1160 (1995)
3. Shpaer, E.G., Robinson, M., Yee, D., Candlin, J.D., Mines, R., Hunkapiller, T.: Sensitivity and selectivity in protein similarity searches: A comparison of Smith-Waterman in hardware to BLAST and FASTA. Genomics 38, 179-191 (1996)
4. Needleman, S.B., Wunsch, C.D.: A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology 48(3), 443-453 (1970)
5. Smith, T.F., Waterman, M.S.: Identification of common molecular subsequences. Journal of Molecular Biology 147(1), 195-197 (1981)
6. Van Court, T., Herbordt, M.C.: Families of FPGA-based accelerators for approximate string matching. Microprocessors & Microsystems 31, 135-145 (2007)
7. ALTERA. Implementation of the smith-waterman algorithm on a reconfigurable supercomputing platform (September 2007)
8. Benkrid, K., Liu, Y., Benkrid, A.: A highly parameterised and efficient FPGA-based skeleton for pairwise biological sequence alignment. IEEE Transactions on Very Large Scale Integration (VLSI Systems) 17(4), 561-570 (2009)
9. Ligowski, Ł., Rudnicki, W.R.: An efficient implementation of smith waterman algorithm on GPU using CUDA, for massively parallel scanning of sequence databases. In: Proceedings of the IEEE International Symposium on Parallel and Distributed Processing (appeared in HICOMB), pp. 1-8 (May 2009)
10. Liu, Y., Maskell, D.L., Schmidt, B.: CUDASW++: optimizing smith-waterman sequence database searches for CUDA-enabled graphics processing units. BMC Research Notes 2(1), 73-82 (2009)
11. Ligowski, Ł., Rudnicki, W.R.: GPU-SW sequence alignment server. In: Proceedings of International Conference on Computational Science, pp. 1-10 (June 2010)
12. Dohi, K., Benkrid, K., Ling, C., Hamada, T., Shibata, Y.: Highly efficient mapping of the smith-waterman algorithm on CUDA-compatible GPUs. In: Proceedings of the IEEE International Conference on Application-specific Systems Architectures and Processors, pp. 29-36 (July 2010)
13. Aldinucci, M., Danelutto, M., Meneghin, M., Kilpatrick, P., Torquati, M.: Efficient streaming applications on multi-core with fastflow: the biosequence alignment test-bed. In: Proceedings of International Conference on Parallel Computing, pp. 273-280 (September 2009)
14. Dayhoff, M.O., Schwartz, R.M., Orcutt, B.C.: A model of evolutionary change in proteins, vol. 5. National Biomedical Research Foundation (1978)
15. Altschul, S.F.: Amino acid substitution matrices from an information theoretic perspective. Journal of Molecular Biology 219(3), 555-565 (1991)
16. Gotoh, O.: An improved algorithm for matching biological sequences. Journal of Molecular Biology 162(3), 705-708 (1982)
17. Jacob, A.C., Buhler, J.D., Chamberlain, R.D.: Design of throughput-optimized arrays from recurrence abstractions. In: Proceedings of the IEEE International Conference on Application-specific Systems Architectures and Processors, pp. 133-140 (July 2010)
18. Manavski, S.A., Valle, G.: CUDA compatible GPU cards as efficient hardware accelerators for smith-waterman sequence alignment. BMC Bioinformatics 9(suppl. 2), S10 (2008)