DocumentCode
2330119
Title
Porting Autodock to CUDA
Author
Kannan, Sarnath ; Ganji, Raghavendra
Author_Institution
HCL Technol., Bangalore, India
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
8
Abstract
This paper is a report on the migration of the molecular docking application, “Autodock” to NVIDIA CUDA. Autodock is a Drug Discovery Tool that uses a Genetic Algorithm to find the optimal docking position of a ligand to a protein. Speedup of Autodock greatly benefits the drug discovery process. In this paper, we show how significant speed up of Autodock can be achieved using NVIDIA CUDA. This paper describes the strategy of porting the Genetic Algorithm to CUDA. Three different parallel design alternatives are discussed. The resultant implementation features ~50x speedup on the fitness function evaluation and 10x to 47x speedup on the core genetic algorithm.
Keywords
genetic algorithms; parallel architectures; proteins; NVIDIA CUDA; drug discovery tool; genetic algorithm; molecular docking application; porting autodock; protein; Genetics; Graphics processing unit; Hardware; Instruction sets; Interpolation; Kernel; Three dimensional displays;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location
Barcelona
Print_ISBN
978-1-4244-6909-3
Type
conf
DOI
10.1109/CEC.2010.5586277
Filename
5586277
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