Title :
Porting Autodock to CUDA
Author :
Kannan, Sarnath ; Ganji, Raghavendra
Author_Institution :
HCL Technol., Bangalore, India
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;
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
DOI :
10.1109/CEC.2010.5586277