arrow
返回

A High-Performance Parallel-Generalized Born Implementation Enabled by Tabulated Interaction Rescaling

delete2010-08-19
delete21
PRE
AI
P
Per Larsson
E
Erik Lindahl *
DOI:10.1002/jcc.21552delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Implicit solvent representations, in general, and generalized Born models, in particular, provide an attractive way to reduce the number of interactions and degrees of freedom in a system. The instantaneous relaxation of the dielectric shielding provided by an implicit solvent model can be extremely efficient for high-throughput and Monte Carlo studies, and a reduced system size can also remove a lot of statistical noise. Despite these advantages, it has been difficult for generalized Born implementations to significantly outperform optimized explicit-water simulations due to more complex functional forms and the two extra interaction stages necessary to calculate Born radii and the derivative chain rule terms contributing to the force. Here, we present a method that uses a rescaling transformation to make the standard generalized Born expression a function of a single variable, which enables an efficient tabulated implementation on any modern CPU hardware. The total performance is within a factor 2 of simulations in vacuo. The algorithm has been implemented in Gromacs, including single-instruction multiple-data acceleration, for three different Born radius models and corresponding chain rule terms. We have also adapted the model to work with the virtual interaction sites commonly used for hydrogens to enable long-time steps, which makes it possible to achieve a simulation performance of 0.86 mu s/day for BBA5 with 1-nm cutoff on a single quad-core desktop processor. Finally, we have also implemented a set of streaming kernels without neighborlists to accelerate the non-cutoff setup occasionally used for implicit solvent simulations of small systems. (C) 2010 Wiley Periodicals, Inc. J Comput Chem 31: 2593-2600, 2010
Keyword:
generalized born
tabulation
molecular dynamics
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Journal of Computational Chemistry 封面图
Journal of Computational Chemistry
IF:
4.8
论文数:
7.1K
被引数:
6.1W

机构

S
Stockholm University
学者数:
1.8W
论文数: 1.7W
被引数: 32
引用论文

引用论文

Implicit solvent models
err1999-04-01
err819
PREAI
errRoux, B; Simonson, T
err分享
err收藏
err分享
err收藏
err分享
err收藏
Caffeine, Cycling Performance, and Exogenous CHO Oxidation
err2009-09-01
err0
errOAAI
errBEN DESBROW; CLARE M. BARRETT; CLARE L. MINAHAN; GARY D. GRANT; MICHAEL D. LEVERITT
err分享
err收藏
Efficient generalized Born models for Monte Carlo simulations
err2006-04-08
err31
PREAI
errMichel, Julien; Taylor, Richard D.; Essex, Jonathan W.
err分享
err收藏
err分享
err收藏
学者 查看更多内容