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Driving solar coronal MHD simulations on high-performance computers

机译:在高性能电脑上驾驶太阳冠MHD模拟

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The quality of today's research is often tightly limited to the available computing power and scalability of codes to many processors. For example, tackling the problem of heating the solar corona requires a most realistic description of the plasma dynamics and the magnetic field. Numerically solving such a magneto-hydrodynamical (MHD) description of a small active region (AR) on the Sun requires millions of computation hours on current high-performance computing (HPC) hardware. The aim of this work is to describe methods for an efficient parallelisation of boundary conditions and data input/output (IO) strategies that allow for a better scaling towards thousands of processors (CPUs). The Pencil Code is tested before and after optimisation to compare the performance and scalability of a coronal MHD model above an AR. We present a novel boundary condition for non-vertical magnetic fields in the photosphere, where we approach the realistic pressure increase below the photosphere. With that, magnetic flux bundles become narrower with depth and the flux density increases accordingly. The scalability is improved by more than one order of magnitude through the HPCfriendly boundary conditions and IO strategies. This work describes also the necessary nudging methods to drive the MHD model with observed magnetic fields from the Sun's photosphere. In addition, we present the upper and lower atmospheric boundary conditions (photospheric and towards the outer corona), including swamp layers to diminish perturbations before they reach the boundaries. Altogether, these methods enable more realistic 3D MHD simulations than previous models regarding the coronal heating problem above an AR - simply because of the ability to use a large amount of CPUs efficiently in parallel.
机译:今天的研究的质量通常紧密地限于可用的计算能力和代码的可扩展性到许多处理器。例如,解决太阳能电晕的问题需要对等离子体动力学和磁场的最逼真的描述。数值求解太阳上的小型有源区(AR)的磁动力学(MHD)描述需要在当前的高性能计算(HPC)硬件上数百万计算时间。这项工作的目的是介绍边界条件和数据输入/输出(IO)策略的有效平行的方法,这些策略允许成千上万的处理器(CPU)更好地缩放。在优化之前和之后测试铅笔代码,以比较AR上方的冠状MHD模型的性能和可扩展性。我们为Photosphere中的非垂直磁场提出了一种新的边界条件,在那里我们接近Photosphere以下的现实压力增加。因此,磁通束与深度变窄,磁通密度相应地增加。通过HPC Friendly边界条件和IO策略,通过一个以上级别提高了可扩展性。这项工作还描述了使用来自Sun的Photosphere的观察到的磁场驱动MHD模型的必要的亮度方法。此外,我们介绍了上部和下部大气边界条件(拍摄体和朝向外部电晕),包括沼泽层,以在达到边界之前减少扰动。完全,这些方法能够比以前的模型更具现实的3D MHD模拟,这是关于AR上方的冠状加热问题的模拟 - 仅仅是因为能够有效地平行使用大量CPU。

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