Saini et al. compared a range of Intel server processors using diverse microbenchmarks, proxy apps, and application codes. We extend their methodology towards Cascade Lake SP and also focus on application-near scenarios. Hofmann et al. presented microbenchmark results for several Intel server CPUs. Molka et al. used their BenchIT microbenchmarking framework to thoroughly analyze latency and bandwidth across the full memory hierarchy of Intel Sandy Bridge and AMD Bulldozer processors, but no application analysis or performance modeling was done. The following papers present and analyze microbenchmark and application performance data in order to fathom the capabilities of the hardware. There is a vast body of research on benchmarking of HPC systems. 6 we then revisit the findings and see how they affect code from realistic applications. 2, microarchitectural analysis using microbenchmarks (e.g., load and copy kernels and STREAM) is performed in Sect. After describing the benchmark systems setup in Sect. Using the model we identify an MPI desynchronization mechanism in the implementation that causes erratic performance of one solver component. To understand the performance characteristics of the HPCG benchmark, we construct and validate the roofline model for all its components and the full solver for the first time. This paper makes the following relevant contributions: Probably the biggest modification in this respect was the introduction of a new 元 cache design. Our microbenchmarking results highlight the changes from the Broadwell to the Cascade Lake architecture and their impact on the performance of HPC applications. We also show how simple performance models can help to draw correct conclusions from the data. During the process we demonstrate the different aspects of proper benchmarking like the importance of appropriate tools, the danger of black-box benchmark code, and the influence of different hardware and system settings. In this paper we explore two modern Intel server processors, Cascade Lake SP and Broadwell EP, using carefully developed micro-architectural benchmarks, then show how these simple microbenchmark codes become relevant in application scenarios. However, with hardware becoming more diverse, proper benchmarking is challenging and error-prone due to wide variety of available but often badly documented tuning knobs and settings. Benchmarking the architectures to understand their characteristics is pivotal for informed decision making and targeted code optimization. This trend is believed to continue in the future with more vendors such as Marvell, Huawei, and Arm entering HPC and related fields with new designs. All of these chips have different performance-power-price points, and thus different performance characteristics. Over the past few years the field of high performance computing (HPC) has received attention from different vendors, which led to a steep rise in the number of chip architectures. Finally we use DGEMM, sparse matrix-vector multiplication, and the HPCG benchmark to make a connection to relevant application scenarios. The new victim 元 cache of Cascade Lake and its advanced replacement policy receive due attention. 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. In this paper we investigate two modern Intel x86 server CPU architectures in depth: Broadwell EP and Cascade Lake SP. The insight gained from microbenchmarks may then be applied to real applications for performance analysis or optimization. Microbenchmarks, 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. 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. Hardware platforms in high performance computing are constantly getting more complex to handle even when considering multicore CPUs alone.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |