Martini straight: Boosting performance using a shorter cutoff and GPUs
| Autor: | Djurre H. de Jong, Helgi I. Ingólfsson, Svetlana Baoukina, Siewert J. Marrink |
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| Přispěvatelé: | Molecular Dynamics |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Physics Boosting (machine learning) Speedup 010304 chemical physics Computation Coarse-grain General Physics and Astronomy 01 natural sciences Energy conservation 03 medical and health sciences symbols.namesake Molecular dynamics 030104 developmental biology Hardware and Architecture 0103 physical sciences symbols Verlet integration Cutoff Lennard-Jones Statistical physics Gromacs van der Waals force Verlet neighbor search |
| Zdroj: | Computer Physics Communications, 199, 1-7. ELSEVIER SCIENCE BV |
| ISSN: | 0010-4655 |
| DOI: | 10.1016/j.cpc.2015.09.014 |
| Popis: | In molecular dynamics simulations, sufficient sampling is of key importance and a continuous challenge in the field. The coarse grain Martini force field has been widely used to enhance sampling. In its original implementation, this force field applied a shifted Lennard-Jones potential for the non-bonded van der Waals interactions, to avoid problems related to a relatively short cutoff. Here we investigate the use of a straight cutoff Lennard-Jones potential with potential modifiers. Together with a Verlet neighbor search algorithm, the modified potential allows the use of GPUs to accelerate the computations in Gromacs. We find that this alternative potential has little influence on most of the properties studied, including partitioning free energies, bulk liquid properties and bilayer properties. At the same time, energy conservation is kept within reasonable bounds. We conclude that the newly proposed straight cutoff approach is a viable alternative to the standard shifted potentials used in Martini, offering significant speedup even in the absence of GPUs. |
| Databáze: | OpenAIRE |
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