Local alignment tool based on Hadoop framework and GPU architecture

Che Lun Hung*, Guan Jie Hua

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

11 Scopus citations

Abstract

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.

Original languageEnglish
Article number541490
JournalBioMed Research International
Volume2014
DOIs
StatePublished - 2014
Externally publishedYes

Fingerprint

Dive into the research topics of 'Local alignment tool based on Hadoop framework and GPU architecture'. Together they form a unique fingerprint.

Cite this