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Highly parallel structured adaptive mesh refinement using parallel language-based approaches

机译:使用基于并行语言的方法进行高度并行的结构化自适应网格细化

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Adaptive Mesh Refinement (AMR) calculations carried out on structured meshes play an exceedingly important role in several areas of science and engineering. This is so not just because AMR techniques allow us to carry out calculations very efficiently but also because they model very precisely the multi-scale fashion in which nature itself works. Many AMR applications are also amongst the most computationally intensive calculations undertaken making it necessary to use parallel supercomputers for their solution. While class library-based approaches are being attempted for parallel AMR we point out here that recent advances in the Fortran 90/95 standard and the OpenMP standard now make it possible to carry out highly parallel AMR calculations using language-based approaches. The language-based ap- proaches offer several advantages over library-based approaches, the two principal ones being portability across parallel platforms and the best possible utilization of Distributed Shared Memory (DSM) hardware on machines that have such hardware. They also free up the ap- plications scientist from being constrained by the static features of a class library. The choice of Fortran also ensures maximal reuse of pre-existing Fortran 77 applications and full Fortran 77-based processing efficiency on each computational node. Our implementation of the ideas presented here in the first author's RIEMANN framework essentially permits any serial, uniform grid, stencil-based Fortran code to be turned into a parallel AMR code. In this paper we first describe our strategy for using Fortran 90 in an object-oriented fashion.
机译:在结构化网格上进行的自适应网格细化(AMR)计算在科学和工程学的多个领域中发挥着极其重要的作用。这不仅是因为AMR技术使我们能够非常有效地执行计算,而且还因为它们非常精确地模拟了自然界自身运作的多尺度方式。许多AMR应用程序也是计算量最大的计算之一,因此有必要使用并行超级计算机作为其解决方案。在尝试针对并行AMR的基于类库的方法时,我们在这里指出,Fortran 90/95标准和OpenMP标准的最新进展现在使使用基于语言的方法进行高度并行的AMR计算成为可能。与基于库的方法相比,基于语言的方法具有多个优点,其中两个主要的方法是跨并行平台的可移植性以及在具有此类硬件的计算机上对分布式共享内存(DSM)硬件的最佳利用。他们还使应用科学家摆脱了类库的静态功能的束缚。选择Fortran还可以确保最大程度地重用现有的Fortran 77应用程序,并确保每个计算节点上具有完整的基于Fortran 77的处理效率。我们在第一作者的RIEMANN框架中提出的想法的实现实质上允许将任何基于序列,统一网格,基于模板的Fortran代码转换为并行AMR代码。在本文中,我们首先描述以面向对象的方式使用Fortran 90的策略。

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