在高性能计算资源上的转向仿真

Junyi Han
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引用次数: 2

摘要

数值模拟的计算转向(CS)在过去三十年中得到了发展。虽然它在一些主要目标上取得了成功,但CS的吸收和影响并没有预期的那么大。本文旨在调查其原因,并从这一分析中提供一个增强的CS框架,同时考虑到终端用户设备的现代发展和超大型高性能计算(HPC)系统(超级计算机)体系结构的变化。我们还考虑了最近对动态数据驱动应用系统(DDDAS)和网络物理系统(CPS)的兴趣对CS的影响。作为我们研究的开始阶段,我们提出了一个通用框架,将CS和HPC作为Web服务提供,以扩大它们的吸收和使用。这种方法的主要优点包括可重用性、模块化、实时3D web可视化,以及使用户能够在便携式设备上访问CS和HPC服务。
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Steering simulations on high performance computing resources
Computational Steering (CS) of numerical simulations has been developed over the last three decades. While it has succeeded in some of its chief aims, the uptake and impact of CS has not been as great as anticipated. This paper aims to investigate the reasons for this, and from this analysis to provide an enhanced CS framework, taking into account both modern developments in end-user devices and changes in the architecture of very large High Performance Computing (HPC) systems (supercomputers). We also consider the impact on CS of the recent interest in Dynamic Data Driven Application Systems (DDDAS) and Cyber-Physical System (CPS). As the beginning phase of our research, we present a general-purpose framework that provides CS and HPC as Web services to widen their uptake and use. Key advantages of this approach, include the re-usability, modularity, real-time 3D web visualization, and capacitating users to access CS and HPC service on portable devices.
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