Greedy replica exchange algorithm for heterogeneous computing grids.
Greedy replica exchange algorithm for heterogeneous computing grids.
复制标题
异构计算网格的贪婪副本交换算法。
DOI：
10.1007/s00894-015-2763-5
复制
发表时间：
2015
影响因子：
2.2
通讯作者：
Klimov,DmitriK
中科院分区：
文献类型：
--
作者：
Lockhart,Christopher;O'Connor,James;Armentrout,Steven;Klimov,DmitriK
副本交换分子动力学(REMD)已成为研究复杂生物分子系统的重要工具。然而，分布式计算环境的异构性限制了其在分布式计算网格上的应用。在这项研究中，我们提出了一种适用于异质网格计算的REMD实现，称为贪婪REMD(GREMD)。为了分散副本管理，gREMD利用预先计算的温度之间的交换尝试计划。我们将GREMD与标准REMD进行了比较，得出了四个主要结论。首先，gREMD将网格REMD模拟的速度提高了40%。其次，gREMD将网格REMD中的CPU利用率提高了高达60%。第三，我们认为随着副本数量的增加，gREMD有望保持大致恒定的CPU利用率和模拟挂钟时间。最后，我们证明了gREMD正确地实现了REMD算法，并再现了我们以前的标准REMD模拟中采样的短肽的构象集成。图形摘要标准副本交换分子动力学(REMD)通常要求所有副本在副本交换协议启动之前完成。贪婪的REMD分散了这一过程，因此只需要一个副本及其预定的交换伙伴在启动副本交换之前完成模拟。由于贪婪REMD减少了与副本交换任务相关的空闲时间，因此它特别适合在异类分布式计算环境中执行REMD。
Replica exchange molecular dynamics (REMD) has become a valuable tool in studying complex biomolecular systems. However, its application on distributed computing grids is limited by the heterogeneity of this environment. In this study, we propose a REMD implementation referred to as greedy REMD (gREMD) suitable for computations on heterogeneous grids. To decentralize replica management, gREMD utilizes a precomputed schedule of exchange attempts between temperatures. Our comparison of gREMD against standard REMD suggests four main conclusions. First, gREMD accelerates grid REMD simulations by as much as 40 %. Second, gREMD increases CPU utilization rates in grid REMD by up to 60 %. Third, we argue that gREMD is expected to maintain approximately constant CPU utilization rates and simulation wall-clock times with the increase in the number of replicas. Finally, we show that gREMD correctly implements the REMD algorithm and reproduces the conformational ensemble of a short peptide sampled in our previous standard REMD simulations. We believe that gREMD can find its place in large-scale REMD simulations on heterogeneous computing grids.Graphical AbstractStandard replica exchange molecular dynamics (REMD) typically requires all replicas to complete prior to initiation of the replica exchange protocol. Greedy REMD decentralizes this process and therefore only requires a replica and its predetermined exchange partner to have finished simulations prior to initiating replica exchange. Because greedy REMD reduces the idle time associated with replica exchange tasks, it becomes particularly well suited for performing REMD on heterogeneous distributed computing environments.