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Enabling Large-Scale Biomolecular Conformation Search with Replica Exchange Statistical Temperature Molecular Dynamics (RESTMD) over HPC and Cloud Computing Resources

机译:通过HPC和云计算资源上的副本交换统计温度分子动力学(RESTMD)启用大规模生物分子构象搜索

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We present the latest development and experimental simulation studies of Statistical Temperature Molecular Dynamics (STMD) and its parallel tempering version, Replica Exchange Statistical Temperature Molecular Dynamics (RESTMD). Our main contributions are i) introduction of newly implemented STMD in LAMMPS, ii) use of large scale distributed cyber infrastructure including Amazon EC2 and the nationwide distributed computing infrastructure GENI, in addition to High-performance Computing (HPC) cluster systems, and iii) benchmark and simulation results highlighting advantages and potentials of STMD and RESTMD for challenging large-scale bio molecular conformational search. In this work, we attempt to provide convincing evidence that RESTMD, combining two advanced sampling protocols, STMD and the replica exchange algorithm, offers various advantages over not only conventional ineffective approaches but also other enhanced sampling methods. Interestingly, RESTMD has benefits over the most popular Replica Exchange Molecular Dynamics (REMD) as an application maximizing its capacity in HPC environments. For example, RESTMD alleviates the need of a large number of replicas which is unavoidable in REMD and is flexible in order to exploit the maximum amount of available computing power of a cluster system. Continuing our recent effort in which RESTMD was implemented with a community molecular dynamics package, CHARMM, and the Hadoop MapReduce, in this work, we report latest development outcomes. First of all, we plugged the implementation of STMD into LAMMPS, one of the most popular public molecular dynamics packages. This is expected to position STMD and RESTMD appealing to investigators from a broad range of life science fields. Secondly, Hadoop MapReduce-based RESTMD is now able to run on Amazon EC2 and the nationwide network virtual organization, the GENI distributed computing environment. Thirdly, in order to find optimized parameters for RESTMD simulations, simulation re- ults using test systems, water and solvated cram bin, were obtained and presented. These results, despite of relatively small sizes and short time scale trajectories, serve to underscore merits and potentials of STMD and RESTMD with respect to the strength in algorithmic advantages as well as efficient utilization of distributed resources.
机译:我们介绍统计温度分子动力学(STMD)及其并行回火版本副本交换统计温度分子动力学(RESTMD)的最新开发和实验模拟研究。我们的主要贡献是:i)在LAMMPS中引入新实施的STMD,ii)除了高性能计算(HPC)集群系统之外,还使用包括Amazon EC2和全国性分布式计算基础设施GENI在内的大规模分布式网络基础设施,以及iii)基准测试和模拟结果突出了STMD和RESTMD在挑战大规模生物分子构象搜索中的优势和潜力。在这项工作中,我们试图提供令人信服的证据,证明RESTMD结合了两种高级采样协议(STMD和副本交换算法),不仅具有传统的无效方法而且还具有其他增强的采样方法所不具备的各种优势。有趣的是,RESTMD具有比最流行的副本交换分子动力学(REMD)更大的优势,因为该应用程序可最大化其在HPC环境中的容量。例如,RESTMD减轻了REMD中不可避免的大量副本的需求,并且可以灵活地利用集群系统的最大可用计算能力。继续我们最近使用社区分子动力学软件包CHARMM和Hadoop MapReduce实施RESTMD的工作,在此工作中,我们报告了最新的开发成果。首先,我们将STMD的实现插入到LAMMPS中,LAMMPS是最受欢迎的公共分子动力学软件包之一。预计这将使STMD和RESTMD吸引来自广泛生命科学领域的研究人员。其次,基于Hadoop MapReduce的RESTMD现在可以在Amazon EC2和全国性网络虚拟组织GENI分布式计算环境上运行。第三,为了找到用于RESTMD模拟的优化参数,获得并给出了使用测试系统,水和溶剂化缸的模拟结果。尽管具有相对较小的尺寸和较短的时间尺度轨迹,但这些结果仍可强调STMD和RESTMD在算法优势以及对分布式资源的有效利用方面的优点和潜力。

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