TY - GEN
T1 - Accelerating Dock6's Amber scoring with graphic processing unit
AU - Yang, Hailong
AU - Li, Bo
AU - Wang, Yongjian
AU - Luan, Zhongzhi
AU - Qian, Depei
AU - Chu, Tianshu
PY - 2010
Y1 - 2010
N2 - In the drug discovery field, solving the problem of virtual screening is a long term-goal. The scoring functionality which evaluates the fitness of the docking result is one of the major challenges in virtual screening. In general, scoring functionality in docking requires large amount of floating-point calculations and usually takes several weeks or even months to be finished. This time-consuming disadvantage is unacceptable especially when highly fatal and infectious virus arises such as SARS and H1N1. This paper presents how to leverage the computational power of GPU to accelerate Dock6 [1]'s Amber [2] scoring with NVIDIA CUDA [3] platform. We also discuss many factors that will greatly influence the performance after porting the Amber scoring to GPU, including thread management, data transfer and divergence hidden. Our GPU implementation shows a 6.5x speedup with respect to the original version running on AMD dual-core CPU for the same problem size.
AB - In the drug discovery field, solving the problem of virtual screening is a long term-goal. The scoring functionality which evaluates the fitness of the docking result is one of the major challenges in virtual screening. In general, scoring functionality in docking requires large amount of floating-point calculations and usually takes several weeks or even months to be finished. This time-consuming disadvantage is unacceptable especially when highly fatal and infectious virus arises such as SARS and H1N1. This paper presents how to leverage the computational power of GPU to accelerate Dock6 [1]'s Amber [2] scoring with NVIDIA CUDA [3] platform. We also discuss many factors that will greatly influence the performance after porting the Amber scoring to GPU, including thread management, data transfer and divergence hidden. Our GPU implementation shows a 6.5x speedup with respect to the original version running on AMD dual-core CPU for the same problem size.
UR - https://www.scopus.com/pages/publications/78951470079
U2 - 10.1007/978-3-642-13119-6_35
DO - 10.1007/978-3-642-13119-6_35
M3 - 会议稿件
AN - SCOPUS:78951470079
SN - 3642131182
SN - 9783642131189
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 404
EP - 415
BT - Algorithms and Architectures for Parallel Processing - 10th International Conference, ICA3PP 2010, Proceedings
T2 - 10th International Conference Algorithms and Architectures for Parallel Processing, ICA3PP 2010
Y2 - 21 May 2010 through 23 May 2010
ER -