Protein sequence alignment with GPU: database optimization / Ahmad Faiz Mohd Rahi
This paper present a protein sequence alignment accelerated with Graphics Processing Units (GPUs). In bioinformatics, alignments are commonly performed in genome and protein sequence analysis for gene identification and evolutionary similarities. For such analysis, there are a few approaches, every...
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| Format: | Thesis |
| Language: | en |
| Published: |
2014
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/115800/1/115800.pdf https://ir.uitm.edu.my/id/eprint/115800/ |
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| Summary: | This paper present a protein sequence alignment accelerated with Graphics Processing Units (GPUs). In bioinformatics, alignments are commonly performed in genome and protein sequence analysis for gene identification and evolutionary similarities. For such analysis, there are a few approaches, every single different in accuracy and computational difficulty. Smith-waterman (SW) considered as the greatest algorithm for its accuracy in same scoring. In the other hand, it is not suitable to be used by life scientists as it is experience executions time on general purposed. Through this paper we focus on SmithWaterman to discover the construction features of Graphic Processing Units (GPUs) and determine the difficulties in the hardware construction as well as the software improvements needed to put on the program construction on the GPU. In comparison with the state-of-the-art implementation on an NVIDIA Geforce 610M graphics card, our implementation reports a 1.9 times performance improvement in terms of execution time. |
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