标题： ECM模型在A64FX上对SpMV和格点QCD的性能调优 显示英文标题

标题： ECM modeling and performance tuning of SpMV and Lattice QCD on A64FX

摘要： A64FX CPU可以说是迄今为止最强大的基于Arm的处理器设计。 尽管它是一款传统的基于缓存的多核处理器，但其峰值性能和内存带宽可与加速器设备相媲美。 对于希望充分利用其全部潜力的开发人员来说，对其性能特征有很好的理解至关重要。 我们通过对用于富士通FX1000超级计算机中的A64FX的架构分析，达到了可以构建执行-缓存-内存（ECM）性能模型的详细程度，该模型适用于稳态循环。 在此过程中，我们识别出了一些架构上的特点，这些特点指出了可行的通用优化策略。 在使用简单的流式循环验证了模型之后，我们将获得的洞察应用于稀疏矩阵向量乘法（SpMV）和量子色动力学（QCD）中的域壁（DW）内核。 对于SpMV，我们展示了为什么在这种架构上CRS矩阵存储格式不是一个好的实际选择，并且如何通过SELL-C-sigma格式实现带宽饱和。 对于DW内核，我们提供了缓存重用分析，并展示了复杂数组的数据布局选择如何在这种情况下也能实现内存带宽饱和。 与最先进的高端Intel Cascade Lake AP和Nvidia V100系统的比较使A64FX的能力得以体现。 我们还探索了利用Fugaku系统提供的调优选项进行功耗优化的潜力，在SpMV中实现了约31%的能量节省，在DW中实现了约18%的能量节省。 显示英文摘要

摘要： The A64FX CPU is arguably the most powerful Arm-based processor design to date. Although it is a traditional cache-based multicore processor, its peak performance and memory bandwidth rival accelerator devices. A good understanding of its performance features is of paramount importance for developers who wish to leverage its full potential. We present an architectural analysis of the A64FX used in the Fujitsu FX1000 supercomputer at a level of detail that allows for the construction of Execution-Cache-Memory (ECM) performance models for steady-state loops. In the process we identify architectural peculiarities that point to viable generic optimization strategies. After validating the model using simple streaming loops we apply the insight gained to sparse matrix-vector multiplication (SpMV) and the domain wall (DW) kernel from quantum chromodynamics (QCD). For SpMV we show why the CRS matrix storage format is not a good practical choice on this architecture and how the SELL-C-sigma format can achieve bandwidth saturation. For the DW kernel we provide a cache-reuse analysis and show how an appropriate choice of data layout for complex arrays can realize memory-bandwidth saturation in this case as well. A comparison with state-of-the-art high-end Intel Cascade Lake AP and Nvidia V100 systems puts the capabilities of the A64FX into perspective. We also explore the potential for power optimizations using the tuning knobs provided by the Fugaku system, achieving energy savings of about 31% for SpMV and 18% for DW.