The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Accelerating molecular modeling applications with graphics processors
Abstract
Molecular mechanics simulations offer a computational approach to study the behavior of biomolecules at atomic detail, but such simulations are limited in size and timescale by the available computing resources. State‐of‐the‐art graphics processing units (GPUs) can perform over 500 billion arithmetic operations per second, a tremendous computational resource that can now be utilized for general purpose computing as a result of recent advances in GPU hardware and software architecture. In this article, an overview of recent advances in programmable GPUs is presented, with an emphasis on their application to molecular mechanics simulations and the programming techniques required to obtain optimal performance in these cases. We demonstrate the use of GPUs for the calculation of long‐range electrostatics and nonbonded forces for molecular dynamics simulations, where GPU‐based calculations are typically 10–100 times faster than heavily optimized CPU‐based implementations. The application of GPU acceleration to biomolecular simulation is also demonstrated through the use of GPU‐accelerated Coulomb‐based ion placement and calculation of time‐averaged potentials from molecular dynamics trajectories. A novel approximation to Coulomb potential calculation, the multilevel summation method, is introduced and compared with direct Coulomb summation. In light of the performance obtained for this set of calculations, future applications of graphics processors to molecular dynamics simulations are discussed. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007
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Cites
VMD: visual molecular dynamics
Humphrey, W., Dalke, A., & Schulten, K. (1996) · Journal of Molecular Graphics · doi:10.1016/0263-7855(96)00018-5 · Cited by 66,952
Self-citationScalable molecular dynamics with NAMD
Phillips, J. C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., Chipot, C., Skeel, R. D., Kalé, L., & Schulten, K. (2005) · Journal of Computational Chemistry · doi:10.1002/jcc.20289 · Cited by 16,914
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Computer Simulation of Liquids
Allen, M. P., & Tildesley, D. J. (2017) · doi:10.1093/oso/9780198803195.001.0001 · Cited by 20,945
(2008) · doi:10.1145/1401132.1401152 · Cited by 1,575
OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems
Stone, J. E., Gohara, D., & Shi, G. (2010) · Computing in Science & Engineering · doi:10.1109/mcse.2010.69 · Cited by 1,086
Self-citationHeterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS
Páll, S., Zhmurov, A., Bauer, P., Abraham, M., Lundborg, M., Gray, A., Hess, B., & Lindahl, E. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0018516 · Cited by 940
Ufimtsev, I. S., & Martinez, T. J. (2009) · Journal of Chemical Theory and Computation · doi:10.1021/ct9003004 · Cited by 916
Metadata
- Authors
- Stone, J. E., Phillips, J. C., Freddolino, L., Hardy, D. J., Trabuco, L. G., & Schulten, K.
- Venue
- Journal of Computational Chemistry
- Publisher
- Wiley
- Published
- 2007-09-25
- Volume
- 28
- Issue
- 16
- Pages
- 2618-2640
- ISSN
- 0192-8651 (ISSN-L)
- 1096-987X
- OpenAlex
- W2159497832
- Cited by
- 739
- References
- 2
- FWCI
- 107.44
- Type
- journal article
- Language
- en
- Open access
- closed
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