TY - JOUR
T1 - Local alignment tool based on Hadoop framework and GPU architecture
AU - Hung, Che Lun
AU - Hua, Guan Jie
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84901790552&partnerID=8YFLogxK
U2 - 10.1155/2014/541490
DO - 10.1155/2014/541490
M3 - 文章
C2 - 24955362
AN - SCOPUS:84901790552
SN - 2314-6133
VL - 2014
JO - BioMed Research International
JF - BioMed Research International
M1 - 541490
ER -