天文物理代码迁移到Exascale时代
Astrophysical code migration into Exascale Era
摘要：
ExaNeSt和EuroExa H2020欧盟资助的项目旨在设计和开发一个基于低能耗ARM 64内核和FPGA加速器的千兆级计算平台原型。我们参与硬件解决方案的应用驱动设计和原型验证。为了进行这项工作，我们正在使用Hy-Nbody，这是一种最先进的直接N体代码。Hy-Nbody的核心算法已经得到改进，使其越来越适合exascale目标平台。在等待ExaNest原型发布之前，我们正在ARM 64 SoC设施上执行测试和代码调优操作：基于64位ARMv 8 Cortex-A72/Cortex-A53内核设计并由Mali-T864嵌入式GPU提供支持的SLURM托管HPC集群。并行地，我们正在FPGA上移植Hy-Nbody内核，旨在测试和比较我们的算法在不同平台上的每瓦性能。在本文中，我们描述了我们如何重新设计的应用程序，我们展示了ARM SoC上的第一个结果。
英文摘要：
The ExaNeSt and EuroExa H2020 EU-funded projects aim to design and develop an exascale ready computing platform prototype based on low-energy-consumption ARM64 cores and FPGA accelerators. We participate in the application-driven design of the hardware solutions and prototype validation. To carry on this work we are using, among others, Hy-Nbody, a state-of-the-art direct N-body code. Core algorithms of Hy-Nbody have been improved in such a way to increasingly fit them to the exascale target platform. Waiting for the ExaNest prototype release, we are performing tests and code tuning operations on an ARM64 SoC facility: a SLURM managed HPC cluster based on 64-bit ARMv8 Cortex-A72/Cortex-A53 core design and powered by a Mali-T864 embedded GPU. In parallel, we are porting a kernel of Hy-Nbody on FPGA aiming to test and compare the performance-per-watt of our algorithms on different platforms. In this paper we describe how we re-engineered the application and we show first results on ARM SoC.
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