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Exploiting computing power of Xeon and Intel Xeon Phi for a Molecular Dynamics Application

机译:利用Xeon和Intel Xeon Phi的计算能力进行分子动力学应用

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Molecular Dynamics (MD) is a computational technique with applicability in fields as diverse as material science, biomolecules and chemical physics. Assisted Model Building with Energy Refinement (AMBER) is an MD package and it uses Message Passing Interface (MPI) to scale in multi-core and cluster environments. In our earlier work [1], we modified one of AMBER's algorithms called Generalized Born (GB) algorithm to run optimally on the Xeon Phi co-processor. This improved performance by 277% on the co-processor. The same changes improved performance on the host server by 80%. In this paper, we extend our earlier work and implement a symmetric solution using both the host server and the co-processor. Since the calculations in GB algorithm involve interactions between all possible atom combinations, it has been very difficult to scale GB algorithm in distributed memory. We evaluate various alternate techniques using combination of MPI and Open Multi-Processing (OpenMP) to get a scalable solution that utilizes the computing power of both the host server as well as the co-processor.
机译:分子动力学(MD)是一种计算技术,具有各种作为材料科学,生物分子和化学物理学的田地。具有能量细化(琥珀色)的辅助模型建筑是MD包,它使用消息传递接口(MPI)来扩展多核和群集环境。在我们之前的工作[1]中,我们修改了琥珀色的算法之一,称为通用出生(GB)算法,在Xeon Phi协处理器上最佳地运行。这种在协处理器上提高了277%的性能。相同的更改将在主机服务器上的性能提高80%。在本文中,我们使用主服务器和协处理器扩展我们之前的工作并实现对称解决方案。由于GB算法的计算涉及所有可能的原子组合之间的相互作用,因此在分布式存储器中缩放GB算法非常困难。我们使用MPI的组合和开放式多处理(OpenMP)进行各种替代技术来获得可伸缩的解决方案,该解决方案利用主机服务器和协处理器的计算能力。

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