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Algorithms of GPU-enabled reactive force field (ReaxFF) molecular dynamics
Zheng, Mo1,2; Li, Xiaoxia1; Guo, Li1
AbstractReactive force field (ReaxFF), a recent and novel bond order potential, allows for reactive molecular dynamics (ReaxFF MD) simulations for modeling larger and more complex molecular systems involving chemical reactions when compared with computation intensive quantum mechanical methods. However, ReaxFF MD can be approximately 10-50 times slower than classical MD due to its explicit modeling of bond forming and breaking, the dynamic charge equilibration at each time-step, and its one order smaller time-step than the classical MD, all of which pose significant computational challenges in simulation capability to reach spatio-temporal scales of nanometers and nanoseconds. The very recent advances of graphics processing unit (GPU) provide not only highly favorable performance for GPU enabled MD programs compared with CPU implementations but also an opportunity to manage with the computing power and memory demanding nature imposed on computer hardware by ReaxFF MD. In this paper, we present the algorithms of GMD-Reax, the first GPU enabled ReaxFF MD program with significantly improved performance surpassing CPU implementations on desktop workstations. The performance of GMD-Reax has been benchmarked on a PC equipped with a NVIDIA C2050 GPU for coal pyrolysis simulation systems with atoms ranging from 1378 to 27,283. GMD-Reax achieved speedups as high as 12 times faster than Duin et al.'s FORTRAN codes in Lammps on 8 CPU cores and 6 times faster than the Lammps' C codes based on PuReMD in terms of the simulation time per time-step averaged over 100 steps. GMD-Reax could be used as a new and efficient computational tool for exploiting very complex molecular reactions via ReaxFF MD simulation on desktop workstations. (C) 2013 Elsevier Inc. All rights reserved.
KeywordReaxff Gpu Computing Gmd-reax Reactive Molecular Dynamics Lammps
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine ; Technology ; Physical Sciences
Indexed BySCI
WOS Research AreaBiochemistry & Molecular Biology ; Computer Science ; Crystallography ; Mathematical & Computational Biology
WOS SubjectBiochemical Research Methods ; Biochemistry & Molecular Biology ; Computer Science, Interdisciplinary Applications ; Crystallography ; Mathematical & Computational Biology
WOS IDWOS:000317795900001
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Cited Times:56[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Proc Engn, State Key Lab Multiphase Complex Syst, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Zheng, Mo,Li, Xiaoxia,Guo, Li. Algorithms of GPU-enabled reactive force field (ReaxFF) molecular dynamics[J]. JOURNAL OF MOLECULAR GRAPHICS & MODELLING,2013,41(0):1-11.
APA Zheng, Mo,Li, Xiaoxia,&Guo, Li.(2013).Algorithms of GPU-enabled reactive force field (ReaxFF) molecular dynamics.JOURNAL OF MOLECULAR GRAPHICS & MODELLING,41(0),1-11.
MLA Zheng, Mo,et al."Algorithms of GPU-enabled reactive force field (ReaxFF) molecular dynamics".JOURNAL OF MOLECULAR GRAPHICS & MODELLING 41.0(2013):1-11.
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