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首页> 外文期刊>Journal of physical chemistry letters >Combining Graphics Processing Units, Simplified Time-Dependent Density Functional Theory, and Finite-Difference Couplings to Accelerate Nonadiabatic Molecular Dynamics
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Combining Graphics Processing Units, Simplified Time-Dependent Density Functional Theory, and Finite-Difference Couplings to Accelerate Nonadiabatic Molecular Dynamics

机译:结合图形处理单元,简化的时间依赖性密度泛函理论和有限差分耦合,以加速非等离的分子动力学

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摘要

Starting from our recently published implementation of nonadiabatic molecular dynamics (NAMD) on graphics processing units (GPUs), we explore further approaches to accelerate ab initio NAMD calculations at the time-dependent density functional theory (TDDFT) level of theory. We employ (1) the simplified TDDFT schemes of Grimme et al. and (2) the Hammes-Schiffer-Tully approach to obtain nonadiabatic couplings from finite-difference calculations. The resulting scheme delivers an accurate physical picture while virtually eliminating the two computationally most demanding steps of the algorithm. Combined with our GPU-based integral routines for SCF, TDDFT, and TDDFT derivative calculations, NAMD simulations of systems of a few hundreds of atoms at a reasonable time scale become accessible on a single compute node. To demonstrate this and to present a first, illustrative example, we perform TDDFT/MM-NAMD simulations of the rhodopsin protein.
机译:从我们最近发布的非等级分子动力学(NAMD)的实施方式在图形处理单元(GPU)上,我们探讨了在时间依赖性密度泛函理论(TDDFT)理论水平上加速AB Initio Namd计算的进一步方法。 我们雇用(1)Grimme等人的简化TDDFT方案。 (2)哈姆斯 - 斯科夫特 - 塔鲁利方法从有限差分计算获得非等压联轴器。 生成的方案可提供精确的物理图像,同时几乎消除了算法的两个计算最苛刻的步骤。 结合我们基于GPU的SCF,TDDFT和TDDFT衍生物计算的基于GPU的整体例程,在单个计算节点上可以在合理的时间尺度上获得几百个原子的系统的NAMD模拟。 为了证明这一点并提供第一,说明性示例,我们对罗多蛋白蛋白的TDDFT / mm-Namd模拟进行。

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