Xu, Y., Wang, D., Janjusic, T., Wu, W., Pei, Y. and Yao, Z. (2017) A Web-Based Visual Analytic Framework for Understanding Large-Scale Environmental Models: A Use Case for the Community Land Model. Procedia Computer Science, 108, 1731-1740.
https://doi.org/10.1016/j.procs.2017.05.181

has been cited by the following article:

• TITLE: Portable Software Environment for Ultrahigh-Resolution ELM Development on GPUs

  AUTHORS: Dali Wang, Peter Schwartz, Fengming Yuan, Franklin Eaglebarge, Danial Riccuito, Peter Thornton, Chris Layton, Qinglei Cao

  KEYWORDS: E3SM Land Model, Ultrahigh-Resolution ELM, Portable Software Environment, GPU-Ready Environment

  JOURNAL NAME: Journal of Computer and Communications, Vol.13 No.2, February 20, 2025

  ABSTRACT: This paper presents our endeavors in developing the large-scale, ultra-high-resolution E3SM Land Model (uELM), specifically designed for exascale computers furnished with accelerators such as Nvidia GPUs. The uELM is a sophisticated code that substantially relies on High-Performance Computing (HPC) environments, necessitating particular machine and software configurations. To facilitate community-based uELM developments employing GPUs, we have created a portable, standalone software environment preconfigured with uELM input datasets, simulation cases, and source code. This environment, utilizing Docker, encompasses all essential code, libraries, and system software for uELM development on GPUs. It also features a functional unit test framework and an offline model testbed for comprehensive numerical experiments. From a technical perspective, the paper discusses GPU-ready container generations, uELM code management, and input data distribution across computational platforms. Lastly, the paper demonstrates the use of environment for functional unit testing, end-to-end simulation on CPUs and GPUs, and collaborative code development.