This paper assesses and reports the experience of ten teams working to port,validate, and benchmark several High Performance Computing applications on a novel GPU-accelerated Arm testbed system. The testbed consists of eight NVIDIA Arm HPC Developer Kit systems built by GIGABYTE, each one equipped with a server-class Arm CPU from Ampere Computing and A100 data center GPU from NVIDIA Corp. The systems are connected together using Infiniband high-bandwidth low-latency interconnect. The selected applications and mini-apps are written using several programming languages and use multiple accelerator-based programming models for GPUs such as CUDA, OpenACC, and OpenMP offloading. Working on application porting requires a robust and easy-to-access programming environment, including a variety of compilers and optimized scientific libraries. The goal of this work is to evaluate platform readiness and assess the effort required from developers to deploy well-established scientific workloads on current and future generation Arm-based GPU-accelerated HPC systems. The reported case studies demonstrate that the current level of maturity and diversity of software and tools is already adequate for large-scale production deployments.
翻译:本文评估并报告10个小组在港口、validate和基准数个高性能计算应用中工作的经验,这些小组在新型的GPU加速式手臂测试系统上工作,测试台由GIGABYTE公司建造的8个NVIDIA Arm HPC开发器系统组成,每个系统都配备了来自Ampeare Economic公司的服务器级 Arm CPU和来自NVIDIA Corporation公司的A100数据中心GPU。这些系统使用Infiniband高波段高频宽度低纬度连接连接连接进行连接。选定的应用程序和微型应用程序使用几种程序语言编写,并使用基于多重加速器的GUDA、OpenACC和OpenMP等GPUPU的编程模型。关于应用应用的安装工作需要一个强大和方便的编程环境,包括各种编程员和优化的科学图书馆。这项工作的目的是评估平台准备情况,评估开发者为在目前和未来的GPU-AC-加速HPC系统上部署固定的科学工作量而需要作出的努力。所报告的案例研究表明,当前和大规模部署的软件的成熟程度已经是相当的成熟和最先进的软件和最先进的软件的成熟和最先进程度。