计算机科学
试验台
移植
编译程序
水准点(测量)
库达
操作系统
程序设计范式
计算机体系结构
英菲尼班德
软件
嵌入式系统
程序设计语言
大地测量学
计算机网络
地理
作者
Wael Elwasif,William F. Godoy,Nick Hagerty,J. Austin Harris,Óscar Hernández,Bálint Joó,Paul R. C. Kent,Damien Lebrun-Grandié,Elijah MacCarthy,Verónica Melesse Vergara,O. E. Bronson Messer,Ross Miller,Sarp Oral,Sergei Bastrakov,Michael Bußmann,Alexander Debus,Klaus Steiniger,Jan Stephan,René Widera,Spencer H. Bryngelson
标识
DOI:10.1145/3581576.3581621
摘要
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, each one equipped with a server-class Arm CPU from Ampere Computing and two data center GPUs from NVIDIA Corp. The systems are connected together using InfiniBand 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.
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