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Understanding HPC Benchmark Performance on Intel Broadwell and Cascade Lake Processors

机译:了解英特尔Broadwell和Cascade Lake处理器上的HPC基准性能

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Hardware platforms in high performance computing are constantly getting more complex to handle even when considering multicore CPUs alone. Numerous features and configuration options in the hardware and the software environment that are relevant for performance are not even known to most application users or developers. Microbench-marks, i.e., simple codes that fathom a particular aspect of the hardware, can help to shed light on such issues, but only if they are well understood and if the results can be reconciled with known facts or performance models. The insight gained from microbenchmarks may then be applied to real applications for performance analysis or optimization. In this paper we investigate two modern Intel x86 server CPU architectures in depth: Broadwell EP and Cascade Lake SP. We highlight relevant hardware configuration settings that can have a decisive impact on code performance and show how to properly measure on-chip and off-chip data transfer bandwidths. The new victim L3 cache of Cascade Lake and its advanced replacement policy receive due attention. Finally we use DGEMM, sparse matrix-vector multiplication, and the HPCG benchmark to make a connection to relevant application scenarios.
机译:即使仅考虑多核CPU,高性能计算中的硬件平台也会变得越来越复杂。大多数应用程序用户或开发人员甚至都不知道与性能相关的硬件和软件环境中的许多功能和配置选项。微基准标记,即能够使硬件的某个特定方面得到体现的简单代码,可以帮助阐明此类问题,但前提是必须很好地理解它们,并且其结果必须与已知的事实或性能模型相一致。从微基准获得的见解可随后应用于实际应用,以进行性能分析或优化。在本文中,我们深入研究了两种现代的Intel x86服务器CPU架构:Broadwell EP和Cascade Lake SP。我们重点介绍了可能对代码性能产生决定性影响的相关硬件配置设置,并展示了如何正确测量片上和片外数据传输带宽。 Cascade Lake的新的受害L3缓存及其高级替换策略受到了应有的重视。最后,我们使用DGEMM,稀疏矩阵矢量乘法和HPCG基准来建立与相关应用程序场景的连接。

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