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在全球分布式高性能计算和可视化环境中,使用皮秒级晶格玻尔兹曼方法研究两亲性立方液晶材料。

Petascale lattice-Boltzmann studies of amphiphilic cubic liquid crystalline materials in a globally distributed high-performance computing and visualization environment.

机构信息

Centre for Computational Science, Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK.

出版信息

Philos Trans A Math Phys Eng Sci. 2010 Aug 28;368(1925):3983-99. doi: 10.1098/rsta.2010.0160.

DOI:10.1098/rsta.2010.0160
PMID:20643689
Abstract

We present very large-scale rheological studies of self-assembled cubic gyroid liquid crystalline phases in ternary mixtures of oil, water and amphiphilic species performed on petascale supercomputers using the lattice-Boltzmann method. These nanomaterials have found diverse applications in materials science and biotechnology, for example, in photovoltaic devices and protein crystallization. They are increasingly gaining importance as delivery vehicles for active agents in pharmaceuticals, personal care products and food technology. In many of these applications, the self-assembled structures are subject to flows of varying strengths and we endeavour to understand their rheological response with the objective of eventually predicting it under given flow conditions. Computationally, our lattice-Boltzmann simulations of ternary fluids are inherently memory- and data-intensive. Furthermore, our interest in dynamical processes necessitates remote visualization and analysis as well as the associated transfer and storage of terabytes of time-dependent data. These simulations are distributed on a high-performance grid infrastructure using the application hosting environment; we employ a novel parallel in situ visualization approach which is particularly suited for such computations on petascale resources. We present computational and I/O performance benchmarks of our application on three different petascale systems.

摘要

我们在 petascale 超级计算机上使用晶格玻尔兹曼方法对油、水和两亲物种的三元混合物中的自组装立方准晶液晶相进行了非常大规模的流变学研究。这些纳米材料在材料科学和生物技术领域有多种应用,例如在光伏器件和蛋白质结晶中。它们作为药物、个人护理产品和食品技术中活性剂的输送载体,越来越受到重视。在许多这些应用中,自组装结构会受到不同强度的流动的影响,我们努力了解它们的流变响应,以便最终在给定的流动条件下预测它。从计算的角度来看,我们对三元流体的晶格玻尔兹曼模拟本质上是内存和数据密集型的。此外,我们对动态过程的兴趣需要远程可视化和分析,以及相关的 TB 级时变数据的传输和存储。我们使用应用程序托管环境在高性能网格基础设施上分布这些模拟,我们采用了一种新颖的并行原位可视化方法,特别适合于在 petascale 资源上进行此类计算。我们在三个不同的 petascale 系统上展示了我们应用程序的计算和 I/O 性能基准。

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