The advantages of the second-generation AMD EPYC Rome processors can be successfully used in the race to Exascale. However, the novel architecture's complexity makes it challenging to adapt demanding scientific codes - like stencil ones - to platforms with Rome CPUs. This article tackles this challenge by exploring the adaptation of the stencil-based CFD (computational fluid dynamics) application called MPDATA to these processors' influential features. We show that the previously proposed parametric adaptation methodology can be profitably applied to extend the performance portability of the memory-bound MPDATA on the AMD EPYC architecture. The extension of the parametric adaptation on the novel architecture requires careful consideration of two relevant aspects that reflect splitting the Rome architecture into multiple dies - features of the cache hierarchy and partitioning cores into work teams. The article also investigates the correlation between the performance optimizations and energy efficiency for a ccNUMA platform powered by top-of-the-line 64-core AMD Rome 7742 CPUs, comparing the results against two servers with Intel Xeon Scalable processors of different generations. Even without appealing to prices, the achieved performance and energy efficiency results are a solid argument confirming the competitiveness of AMD Rome processors against Intel Xeon CPUs in scientific applications.

中文翻译：

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AMD EPYC Rome 上 CFD 应用的架构适应和性能能源优化


第二代AMD EPYC Rome处理器的优势可以在Exascale竞赛中成功发挥。然而，这种新颖架构的复杂性使得将要求严格的科学代码（例如模板代码）适应具有 Rome CPU 的平台变得具有挑战性。本文通过探索名为 MPDATA 的基于模板的 CFD（计算流体动力学）应用程序对这些处理器的影响力功能的适应来应对这一挑战。我们表明，先前提出的参数自适应方法可以有效地应用于扩展 AMD EPYC 架构上内存绑定 MPDATA 的性能可移植性。在新颖架构上扩展参数化适应需要仔细考虑两个相关方面，这两个方面反映了将 Rome 架构拆分为多个芯片 - 缓存层次结构的特征和将核心划分为工作团队的特征。本文还研究了由顶级 64 核 AMD Rome 7742 CPU 驱动的 ccNUMA 平台的性能优化和能效之间的相关性，并将结果与​​配备不同代 Intel Xeon 可扩展处理器的两台服务器进行比较。即使不考虑价格，所取得的性能和能效结果也是证实 AMD Rome 处理器在科学应用中相对于英特尔至强 CPU 的竞争力的有力论据。