Architectural Adaptation and Performance-Energy Optimization for CFD Application on AMD EPYC Rome

Abstract

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 paper 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 paper 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.

Optimizing Data Parallelism for FM-Based Short-Read Alignment on the Heterogeneous Non-Uniform Memory Access Architectures

“…In addition, heterogeneous architectures comprise different kinds of computing nodes with various processor architectures. NUMA processors, such as Intel Xeon and AMD Opteron, can be observed widely used in HPC platforms [31]. These NUMA processors have dedicated local memory banks and local cores, allowing for significant performance improvements in applications like sequence alignment.…”