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Liquid Water: Obtaining the Right Answer for the Right Reasons

机译:液态水:以正确的理由获得正确的答案

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摘要

Water is ubiquitous on our planet and plays an essential role in several key chemical and biological processes. Accurate models for water are crucial in understanding, controlling and predicting the physical and chemical properties of complex aqueous systems. Over the last few years we have been developing a molecular-level based approach for a macroscopic model for water that is based on the explicit description of the underlying intermolecular interactions between molecules in water clusters. In the absence of detailed experimental data for small water clusters, highly-accurate theoretical results are required to validate and parameterize model potentials. As an example of the benchmarks needed for the development of accurate models for the interaction between water molecules, for the most stable structure of (H_2O)_(20) we ran a coupled-cluster calculation on the ORNL's Jaguar peta op computer that used over 100 TB of memory for a sustained performance of 487 TFLOP/s (double precision) on 96,000 processors, lasting for 2 hours. By this summer we will have studied multiple structures of both (H_2O)_(20) and (H_2O)_(24) and completed basis set and other convergence studies and anticipate the sustained performance rising close to 1 PFLOP/s.
机译:水在我们的星球上无处不在,在几个关键的化学和生物过程中起着至关重要的作用。准确的水模型对于理解,控制和预测复杂水系统的物理和化学性质至关重要。在过去的几年中,我们一直在为水的宏观模型开发基于分子水平的方法,该方法基于对水簇中分子之间潜在的分子间相互作用的明确描述。在缺乏有关小型水团的详细实验数据的情况下,需要高度准确的理论结果来验证和参数化模型潜力。作为开发精确的水分子之间相互作用模型所需的基准的一个例子,对于最稳定的(H_2O)_(20)结构,我们在ORNL的Jaguar peta op计算机上进行了耦合聚类计算, 100 TB的内存可在96,000个处理器上实现487 TFLOP / s(双精度)的持续性能,持续2小时。到今年夏天,我们将研究(H_2O)_(20)和(H_2O)_(24)的多个结构,以及完整的基础集和其他收敛性研究,并预计持续性能将接近1 PFLOP / s。

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