11904

Local Alignment Tool Based on Hadoop Framework and GPU Architecture

Che-Lun Hun, Guan-Jie Hua
Department of Computer Science and Communication Engineering, Providence University, Taichung, Taiwan
BioMed Research International, 2014

@article{hung2014local,

   title={Local Alignment Tool Based on Hadoop Framework and GPU Architecture},

   author={Hung, Che-Lun and Hua, Guan-Jie},

   year={2014}

}

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With the rapid growth of next generation sequencing technologies, such as Slex, more and more data have been discovered and published. To analysis 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 by relying 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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