计算机应用研究2024，Vol.41Issue(1)：188-192,205,6.DOI:10.19734/j.issn.1001-3695.2023.05.0200
基于容器技术的水文水动力模型软硬件适配方法
Software and hardware adaptation method of hydrodynamic model based on container technologies
摘要
Abstract
With the development and popularity of advanced RISC machines(ARM),adapting the X86-based scientific com-puting software to ARM-based computing platforms is one of the key issues for scientific research and operational applications.It is urgent to explore the software-hardware-adaptation methods of advanced RISC machines for professional computational models.This paper systematically analysed the key points for software hardware adaptation of ARM.By comparing the existing software adaptation technologies,it selected container technology to enable the hydrodynamic model to run on ARM-based com-puting platforms.Container technology could package the application software and its dependencies into a portable container,which made the suggested software run freely without any dependency on the underlying architecture and operating system.Taking the hydrological hydrodynamic model,TELEMAC,as an example,it explained the principle of Docker image composi-tion in detail,and built the TELEMAC image environment through Dockerfile.The method was verified by carrying out the com-putational cases.The results show that the TELEMAC image can run safely on the Kunpeng 920 processor-based openEuler and Kirin V10.The case calculation results are consistent with the standard results,and the model calculation efficiency is high.The proposed method realizes the adaptation from an X86-based platform to ARM-based computing platforms for professional scientific computing models.This study can also provide a reference for the localization adaptation of other software.关键词
水文水动力模型/国产化适配/TELEMAC软件/镜像环境/Docker技术Key words
hydrodynamic model/local adaptation/TELEMAC software/mirror environment/Docker technology分类
建筑与水利引用本文复制引用
张海嘉,刘家宏,梅超,王佳,高希超..基于容器技术的水文水动力模型软硬件适配方法[J].计算机应用研究,2024,41(1):188-192,205,6.基金项目
国家重点研发计划资助项目(2022YFC3090600) （2022YFC3090600）
国家自然科学基金资助项目(52192671) （52192671）
