Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born

被引:1584
作者
Goetz, Andreas W. [1 ]
Williamson, Mark J. [1 ]
Xu, Dong [1 ]
Poole, Duncan [2 ]
Le Grand, Scott [2 ]
Walker, Ross C. [1 ,3 ]
机构
[1] Univ Calif San Diego, San Diego Supercomp Ctr, La Jolla, CA 92093 USA
[2] NVIDIA Corp, Santa Clara, CA 95050 USA
[3] Univ Calif San Diego, Dept Chem & Biol Chem, La Jolla, CA 92093 USA
基金
美国国家科学基金会;
关键词
SPECIAL-PURPOSE; QUANTUM-CHEMISTRY; FORCE-FIELDS; MODEL; MECHANICS; UBIQUITIN; COMPUTER;
D O I
10.1021/ct200909j
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
We present an implementation of generalized Born implicit solvent all-atom classical molecular dynamics (MD) within the AMBER program package that runs entirely on CUDA enabled NVIDIA graphics processing units (GPUs). We discuss the algorithms that are used to exploit the processing power of the GPUs and show the performance that can be achieved in comparison to simulations on conventional CPU clusters. The implementation supports three different precision models in which the contributions to the forces are calculated in single precision floating point arithmetic but accumulated in double precision (SPDP), or everything is computed in single precision (SPSP) or double precision (DPDP). In addition to performance, we have focused on understanding the implications of the different precision models on the outcome of implicit solvent MD simulations. We show results for a range of tests including the accuracy of single point force evaluations and energy conservation as well as structural properties pertainining to protein dynamics. The numerical noise due to rounding errors within the SPSP precision model is sufficiently large to lead to an accumulation of errors which can result in unphysical trajectories for long time scale simulations. We recommend the use of the mixed-precision SPDP model since the numerical results obtained are comparable with those of the full double precision DPDP model and the reference double precision CPU implementation but at significantly reduced computational cost. Our implementation provides performance for GB simulations on a single desktop that is on par with, and in some cases exceeds, that of traditional supercomputers.
引用
收藏
页码:1542 / 1555
页数:14
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