• 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