TY - GEN
T1 - An Adaptive Hybrid Multiprocessor technique for bioinformatics sequence alignment
AU - Bonny, Mohamed Talal
AU - Salama, Khaled N.
AU - Zidan, Mohammed A.
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2011/2/18
Y1 - 2011/2/18
N2 - Sequence alignment algorithms such as the Smith-Waterman algorithm are among the most important applications in the development of bioinformatics. Sequence alignment algorithms must process large amounts of data which may take a long time. Here, we introduce our Adaptive Hybrid Multiprocessor technique to accelerate the implementation of the Smith-Waterman algorithm. Our technique utilizes both the graphics processing unit (GPU) and the central processing unit (CPU). It adapts to the implementation according to the number of CPUs given as input by efficiently distributing the workload between the processing units. Using existing resources (GPU and CPU) in an efficient way is a novel approach. The peak performance achieved for the platforms GPU + CPU, GPU + 2CPUs, and GPU + 3CPUs is 10.4 GCUPS, 13.7 GCUPS, and 18.6 GCUPS, respectively (with the query length of 511 amino acid). © 2010 IEEE.
AB - Sequence alignment algorithms such as the Smith-Waterman algorithm are among the most important applications in the development of bioinformatics. Sequence alignment algorithms must process large amounts of data which may take a long time. Here, we introduce our Adaptive Hybrid Multiprocessor technique to accelerate the implementation of the Smith-Waterman algorithm. Our technique utilizes both the graphics processing unit (GPU) and the central processing unit (CPU). It adapts to the implementation according to the number of CPUs given as input by efficiently distributing the workload between the processing units. Using existing resources (GPU and CPU) in an efficient way is a novel approach. The peak performance achieved for the platforms GPU + CPU, GPU + 2CPUs, and GPU + 3CPUs is 10.4 GCUPS, 13.7 GCUPS, and 18.6 GCUPS, respectively (with the query length of 511 amino acid). © 2010 IEEE.
UR - http://hdl.handle.net/10754/236113
UR - http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5716098
UR - http://www.scopus.com/inward/record.url?scp=79952565631&partnerID=8YFLogxK
U2 - 10.1109/CIBEC.2010.5716098
DO - 10.1109/CIBEC.2010.5716098
M3 - Conference contribution
SN - 9781424471683
SP - 112
EP - 115
BT - 2010 5th Cairo International Biomedical Engineering Conference
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -