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Foundations of distributed multiscale computing: Formalization,specification, and analysis

机译:分布式多尺度计算的基础:形式化,规范和分析

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Inherently complex problems from many scientific disciplines require a multiscale modeling approach. Yet its practical contents remain unclear and inconsistent. Moreover, multiscale models can be very computationally expensive, and may have potential to be executed on distributed infrastructure. In this paper we propose firm foundations for multiscale modeling and distributed multiscale computing. Useful interaction patterns of multiscale models are made predictable with a submodel execution loop (SEL), four coupling templates, and coupling topology properties. We enhance a high-level and well-defined Multiscale Modeling Language (MML) that describes and specifies multiscale models and their computational architecture in a modular way. The architecture is analyzed using directed acyclic task graphs, facilitating validity checking, scheduling distributed computing resources, estimating computational costs, and predicting deadlocks. Distributed execution using the multiscale coupling library and environment (MUSCLE) is outlined. The methodology is applied to two selected applications in nanotechnology and biophysics, showing its capabilities.
机译:来自许多科学学科的内在复杂问题需要多尺度建模方法。然而,其实际内容仍不清楚和不一致。此外,多尺度模型可能在计算上非常昂贵,并且可能具有在分布式基础架构上执行的潜力。在本文中,我们为多尺度建模和分布式多尺度计算提供了坚实的基础。使用子模型执行循环(SEL),四个耦合模板和耦合拓扑属性,可以预测多尺度模型的有用交互模式。我们增强了高级且定义明确的多尺度建模语言(MML),该语言以模块化方式描述和指定了多尺度模型及其计算体系结构。使用有向无环任务图分析该体系结构,从而促进有效性检查,调度分布式计算资源,估计计算成本并预测死锁。概述了使用多尺度耦合库和环境(MUSCLE)进行的分布式执行。该方法论已应用于纳米技术和生物物理学领域的两个选定应用中,显示了其功能。

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