Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs.
Sequence alignment lies at heart of the bioinformatics. The Smith-Waterman algorithm is one of the key sequence search algorithms and has gained popularity due to improved implementations and rapidly increasing compute power. Recently, the Smith-Waterman algorithm has been successfully mapped onto t...
| Publicado en: | BioMed Research International Vol. 2015; pp. 185179 - 185180 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
1/1/2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109641153&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109641153 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 1/1/2015 vid: 2015 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 109641153 NLM26339591 2013154378 10.1155/2015/185179 NLM26339591 PMC4538332 109641153 ppf: 185179 ppct: 1 formats: fmt: @attributes: type: P tig: atl: Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs. aug: au: Huang, Liang-Tsung Wu, Chao-Chin Lai, Lien-Fu Li, Yun-Ju sug: ab: Sequence alignment lies at heart of the bioinformatics. The Smith-Waterman algorithm is one of the key sequence search algorithms and has gained popularity due to improved implementations and rapidly increasing compute power. Recently, the Smith-Waterman algorithm has been successfully mapped onto the emerging general-purpose graphics processing units (GPUs). In this paper, we focused on how to improve the mapping, especially for short query sequences, by better usage of shared memory. We performed and evaluated the proposed method on two different platforms (Tesla C1060 and Tesla K20) and compared it with two classic methods in CUDASW++. Further, the performance on different numbers of threads and blocks has been analyzed. The results showed that the proposed method significantly improves Smith-Waterman algorithm on CUDA-enabled GPUs in proper allocation of block and thread numbers. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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