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Title

Accelerated GPU Based Protein Sequence Alignment ? An optimized database sequences approach

Author

Muhammad Sadiq Amin, Laiq Hassan, Awais Aziz Shah, Usman Akbar, Hafiz Adnan Niaz

Citation

Vol. 17  No. 10  pp. 231-237

Abstract

Smith-Waterman (S-W) algorithm is the perfect sequence alignment method for the biological database but practically this algorithm lacks pace due to high computational complexity. FASTA, BLAST and other heuristics approaches are faster in computations but less accurate. Volume and length variation of sequences require restructuring the database. Acceleration of Smith-Waterman algorithm on proper modern hardware brings perfection and accuracy. This paper presents a high-performance sequence alignment algorithm implemented on Kepler’s architecture graphic processor unit. This new implementation is improved version having reduced memory accesses to eliminate bandwidth congestion. The implementation is performed on Kepler’s architecture graphics processing unit on which the performance was raised to 51 Giga Cells updates per second GCPUS which is 138.3% increase than the previous implementation on GTX275 GPU. In this implementation protein database is converted into equal length sequence sets on advanced GPU. By this workload is distributed among GPU microprocessor threads. This results in improved implementation than previous implementations.

Keywords

Smith Waterman, SwissProt, Proteins, Sequencing, Alignment, GCPUS, FASTA

URL

http://paper.ijcsns.org/07_book/201710/20171029.pdf