Refactoring the MPS/University of Chicago Radiative MHD (MURaM) model for GPU/CPU performance portability using OpenACC directives
Refactoring the MPS/University of Chicago Radiative MHD (MURaM) model for GPU/CPU performance portability using OpenACC directives
复制标题
使用 OpenACC 指令重构 MPS/芝加哥大学辐射 MHD (MURaM) 模型以实现 GPU/CPU 性能可移植性
DOI：
10.1145/3468267.3470576
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
S. Chandrasekaran
中科院分区：
文献类型：
--
作者：
Eric Wright;D. Przybylski;M. Rempel;Cena Miller;S. Suresh;S. Su;R. Loft;S. Chandrasekaran
MURaM（Max Planck University of芝加哥大学辐射MHD）程序是一个太阳大气辐射MHD模型，已广泛应用于从平静到活跃太阳的太阳现象，包括爆发事件，如耀斑和日冕物质抛射。物理学的处理是足够现实的，允许合成从可见光到极端紫外线和X射线的发射，这是与现有的和未来的多波长观测进行详细比较的关键。该组件严重依赖于MURaM的辐射输运求解器（RTS）;代码中计算量最大的组件。加速RTS的好处是多方面的：更快的RTS允许定期使用与观测进行比较所需的更昂贵的多波段辐射传输，这将为加速RTS的持续改进铺平道路，这对模拟太阳色球层至关重要。我们提出了挑战和策略，以加速多物理场，多波段MURaM使用基于指令的编程模型，OpenACC，以保持跨CPU和GPU的单一源代码。针对2883个测试问题的结果显示，采用优化的RTS例程的MURaM使用单个NVIDIA V100 GPU在完全订阅的40核英特尔Skylake CPU节点上实现了1.73倍的加速，并且就每秒模拟点的数量（以百万计）而言，单个NVIDIA V100 GPU相当于69个Skylake内核。我们还测量了多达96个GPU的并行性能，并给出了弱和强的扩展结果。
The MURaM (Max Planck University of Chicago Radiative MHD) code is a solar atmosphere radiative MHD model that has been broadly applied to solar phenomena ranging from quiet to active sun, including eruptive events such as flares and coronal mass ejections. The treatment of physics is sufficiently realistic to allow for the synthesis of emission from visible light to extreme UV and X-rays, which is critical for a detailed comparison with available and future multi-wavelength observations. This component relies critically on the radiation transport solver (RTS) of MURaM; the most computationally intensive component of the code. The benefits of accelerating RTS are multiple fold: A faster RTS allows for the regular use of the more expensive multi-band radiation transport needed for comparison with observations, and this will pave the way for the acceleration of ongoing improvements in RTS that are critical for simulations of the solar chromosphere. We present challenges and strategies to accelerate a multi-physics, multi-band MURaM using a directive-based programming model, OpenACC in order to maintain a single source code across CPUs and GPUs. Results for a 2883 test problem show that MURaM with the optimized RTS routine achieves 1.73x speedup using a single NVIDIA V100 GPU over a fully subscribed 40-core Intel Skylake CPU node and with respect to the number of simulation points (in millions) per second, a single NVIDIA V100 GPU is equivalent to 69 Skylake cores. We also measure parallel performance on up to 96 GPUs and present weak and strong scaling results.
LFRic：应对天气和气候模型中可扩展性和性能可移植性的挑战
DOI：
10.48550/arxiv.1809.07267
发表时间：
2018
期刊：
arXiv e-prints
影响因子：
--
作者：
Adams S. V.
通讯作者：
Adams S. V.
MPI OpenACC：加速异构系统上的辐射传输微型应用程序、minisweep
影响因子：
6.3
作者：
Searles, Robert;Chandrasekaran, Sunita;Joubert, Wayne;Hernandez, Oscar
通讯作者：
Hernandez, Oscar