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Local Alignment Tool Based on Hadoop Framework and GPU Architecture

With the rapid growth of next generation sequencing technologies, such as Slex, more and more data have been discovered and published. To analyze such huge data the computational performance is an important issue. Recently, many tools, such as SOAP, have been implemented on Hadoop and GPU parallel c...

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Detalles Bibliográficos
Autores principales: Hung, Che-Lun, Hua, Guan-Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4052794/
https://www.ncbi.nlm.nih.gov/pubmed/24955362
http://dx.doi.org/10.1155/2014/541490
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author Hung, Che-Lun
Hua, Guan-Jie
author_facet Hung, Che-Lun
Hua, Guan-Jie
author_sort Hung, Che-Lun
collection PubMed
description With the rapid growth of next generation sequencing technologies, such as Slex, more and more data have been discovered and published. To analyze such huge data the computational performance is an important issue. Recently, many tools, such as SOAP, have been implemented on Hadoop and GPU parallel computing architectures. BLASTP is an important tool, implemented on GPU architectures, for biologists to compare protein sequences. To deal with the big biology data, it is hard to rely on single GPU. Therefore, we implement a distributed BLASTP by combining Hadoop and multi-GPUs. The experimental results present that the proposed method can improve the performance of BLASTP on single GPU, and also it can achieve high availability and fault tolerance.
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spelling pubmed-40527942014-06-22 Local Alignment Tool Based on Hadoop Framework and GPU Architecture Hung, Che-Lun Hua, Guan-Jie Biomed Res Int Research Article With the rapid growth of next generation sequencing technologies, such as Slex, more and more data have been discovered and published. To analyze such huge data the computational performance is an important issue. Recently, many tools, such as SOAP, have been implemented on Hadoop and GPU parallel computing architectures. BLASTP is an important tool, implemented on GPU architectures, for biologists to compare protein sequences. To deal with the big biology data, it is hard to rely on single GPU. Therefore, we implement a distributed BLASTP by combining Hadoop and multi-GPUs. The experimental results present that the proposed method can improve the performance of BLASTP on single GPU, and also it can achieve high availability and fault tolerance. Hindawi Publishing Corporation 2014 2014-05-14 /pmc/articles/PMC4052794/ /pubmed/24955362 http://dx.doi.org/10.1155/2014/541490 Text en Copyright © 2014 C.-L. Hung and G.-J. Hua. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Hung, Che-Lun
Hua, Guan-Jie
Local Alignment Tool Based on Hadoop Framework and GPU Architecture
title Local Alignment Tool Based on Hadoop Framework and GPU Architecture
title_full Local Alignment Tool Based on Hadoop Framework and GPU Architecture
title_fullStr Local Alignment Tool Based on Hadoop Framework and GPU Architecture
title_full_unstemmed Local Alignment Tool Based on Hadoop Framework and GPU Architecture
title_short Local Alignment Tool Based on Hadoop Framework and GPU Architecture
title_sort local alignment tool based on hadoop framework and gpu architecture
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4052794/
https://www.ncbi.nlm.nih.gov/pubmed/24955362
http://dx.doi.org/10.1155/2014/541490
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