86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy
出版年份 2020 全文链接
标题
86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy
作者
关键词
Deep potential, Molecular dynamics, GPU, Heterogeneous architecture, DeePMD-kit
出版物
COMPUTER PHYSICS COMMUNICATIONS
Volume 259, Issue -, Pages 107624
出版商
Elsevier BV
发表日期
2020-09-22
DOI
10.1016/j.cpc.2020.107624
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- TweTriS: Twenty trillion-atom simulation
- (2019) Nikola Tchipev et al. INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS
- Library-Based LAMMPS Implementation of High-Dimensional Neural Network Potentials
- (2019) Andreas Singraber et al. Journal of Chemical Theory and Computation
- SIMPLE-NN: An efficient package for training and executing neural-network interatomic potentials
- (2019) Kyuhyun Lee et al. COMPUTER PHYSICS COMMUNICATIONS
- Structure and dynamics of warm dense aluminum: A molecular dynamics study with density functional theory and deep potential
- (2019) Qianrui Liu et al. JOURNAL OF PHYSICS-CONDENSED MATTER
- Isotope effects in liquid water via deep potential molecular dynamics
- (2019) Hsin-Yu Ko et al. MOLECULAR PHYSICS
- DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics
- (2018) Han Wang et al. COMPUTER PHYSICS COMMUNICATIONS
- The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics
- (2018) Kun Yao et al. Chemical Science
- Tinker-HP: a massively parallel molecular dynamics package for multiscale simulations of large complex systems with advanced point dipole polarizable force fields
- (2018) Louis Lagardère et al. Chemical Science
- Deep Learning for Nonadiabatic Excited-State Dynamics
- (2018) Wen-Kai Chen et al. Journal of Physical Chemistry Letters
- Silicon Liquid Structure and Crystal Nucleation from Ab Initio Deep Metadynamics
- (2018) Luigi Bonati et al. PHYSICAL REVIEW LETTERS
- ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost
- (2017) J. S. Smith et al. Chemical Science
- Machine learning of accurate energy-conserving molecular force fields
- (2017) Stefan Chmiela et al. Science Advances
- Amp : A modular approach to machine learning in atomistic simulations
- (2016) Alireza Khorshidi et al. COMPUTER PHYSICS COMMUNICATIONS
- Strong scaling of general-purpose molecular dynamics simulations on GPUs
- (2015) Jens Glaser et al. COMPUTER PHYSICS COMMUNICATIONS
- A flexible algorithm for calculating pair interactions on SIMD architectures
- (2013) Szilárd Páll et al. COMPUTER PHYSICS COMMUNICATIONS
- Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 2. Explicit Solvent Particle Mesh Ewald
- (2013) Romelia Salomon-Ferrer et al. Journal of Chemical Theory and Computation
- Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
- (2012) Matthias Rupp et al. PHYSICAL REVIEW LETTERS
- \mathcal{O}(N) methods in electronic structure calculations
- (2012) D R Bowler et al. REPORTS ON PROGRESS IN PHYSICS
- Implementing molecular dynamics on hybrid high performance computers – short range forces
- (2010) W. Michael Brown et al. COMPUTER PHYSICS COMMUNICATIONS
- Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons
- (2010) Albert P. Bartók et al. PHYSICAL REVIEW LETTERS
- Anton, a special-purpose machine for molecular dynamics simulation
- (2008) David E. Shaw et al. COMMUNICATIONS OF THE ACM
- TRILLION-ATOM MOLECULAR DYNAMICS BECOMES A REALITY
- (2008) TIMOTHY C. GERMANN et al. INTERNATIONAL JOURNAL OF MODERN PHYSICS C
- GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation
- (2008) Berk Hess et al. Journal of Chemical Theory and Computation
- General purpose molecular dynamics simulations fully implemented on graphics processing units
- (2008) Joshua A. Anderson et al. JOURNAL OF COMPUTATIONAL PHYSICS
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