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Molecular Modeling On Gpu Information

Molecular modeling on GPU is the technique of using a graphics processing unit (GPU) for molecular simulations.[1]

In 2007, NVIDIA introduced video cards that could be used not only to show graphics but also for scientific calculations. These cards include many arithmetic units (currently up to 512) working in parallel. Long before this event, the computational power of video cards was used to accelerate calculations. What was new is that NVIDIA made it possible to develop parallel programs in a high-level language. This technology substantially simplified programming by enabling programs to be written in C/C++.

Quantum chemistry calculations[2][3][4][5][6] and molecular mechanics simulations[7][8][9] (molecular modeling in terms of classical mechanics) are among beneficial applications of this technology. The video cards can accelerate the calculations tens of times. Thus, a PC with such a card has the power similar to that of a cluster of workstations based on the common processors.

Contents

GPU accelerated molecular modelling software

Programs

API

Distributed computing projects

See also

References

  1. ^ John E. Stone, James C. Phillips, Peter L. Freddolino, David J. Hardy 1, Leonardo G. Trabuco, Klaus Schulten (2007). "Accelerating molecular modeling applications with graphics processors". Journal of Computational Chemistry 28 (16): 2618–2640. doi:10.1002/jcc.20829. PMID 17894371.
  2. ^ Koji Yasuda (2008). "Accelerating Density Functional Calculations with Graphics Processing Unit". J. Chem. Theory Comput. 4 (8): 1230–1236. doi:10.1021/ct8001046.
  3. ^ Koji Yasuda (2008). "Two-electron integral evaluation on the graphics processor unit". Journal of Computational Chemistry 29 (3): 334–342. doi:10.1002/jcc.20779. PMID 17614340.
  4. ^ Leslie Vogt, Roberto Olivares-Amaya, Sean Kermes, Yihan Shao, Carlos Amador-Bedolla and Alán Aspuru-Guzik (2008). "Accelerating Resolution-of-the-Identity Second-Order Møller−Plesset Quantum Chemistry Calculations with Graphical Processing Units". J. Phys. Chem. A 112 (10): 2049–2057. doi:10.1021/jp0776762. PMID 18229900.
  5. ^ Ivan S. Ufimtsev and Todd J. Martinez (2008). "Quantum Chemistry on Graphical Processing Units. 1. Strategies for Two-Electron Integral Evaluation". J. Chem. Theo. Comp. 4 (2): 222–231. doi:10.1021/ct700268q.
  6. ^ Ivan S. Ufimtsev and Todd J. Martinez (2008). "Graphical Processing Units for Quantum Chemistry". Comp. Sci. Eng. 10 (6): 26–34. doi:10.1109/MCSE.2008.148.
  7. ^ Joshua A. Anderson, Chris D. Lorenz, A. Travesset (2008). "General Purpose Molecular Dynamics Simulations Fully Implemented on Graphics Processing Units". Journal of Computational Physics 227 (10): 5342–5359. doi:10.1016/j.jcp.2008.01.047.
  8. ^ Christopher I. Rodrigues, David J. Hardy, John E. Stone, Klaus Schulten, and Wen-Mei W. Hwu. (2008). "GPU acceleration of cutoff pair potentials for molecular modeling applications.". In CF'08: Proceedings of the 2008 conference on Computing frontiers, New York, NY, USA: 273–282.
  9. ^ Peter H. Colberg, Felix Höfling (2011). "Highly accelerated simulations of glassy dynamics using GPUs: Caveats on limited floating-point precision". Comp. Phys. Comm. 182 (5): 1120–1129. doi:10.1016/j.cpc.2011.01.009.
  10. ^ http://code.google.com/p/fortrancl/
  11. ^ Octopus 4.0 changelog

External links

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