ERF: Energy Research and Forecasting Model

TL;DR

ERF is a flexible, performance-portable regional atmospheric model leveraging modern HPC architectures, including GPUs, built on the AMReX framework, with verified numerical methods and validation results.

Contribution

The paper introduces ERF, a new atmospheric modeling code optimized for modern HPC systems with GPU support, built on the AMReX framework, and demonstrates its numerical accuracy and validation.

Findings

ERF effectively utilizes GPU acceleration for atmospheric modeling.

The model shows high performance and scalability on modern HPC architectures.

Verification and validation cases confirm ERF's numerical accuracy.

Abstract

High performance computing (HPC) architectures have undergone rapid development in recent years. As a result, established software suites face an ever increasing challenge to remain performant on and portable across modern systems. Many of the widely adopted atmospheric modeling codes cannot fully (or in some cases, at all) leverage the acceleration provided by General-Purpose Graphics Processing Units (GPGPUs), leaving users of those codes constrained to increasingly limited HPC resources. Energy Research and Forecasting (ERF) is a regional atmospheric modeling code that leverages the latest HPC architectures, whether composed of only Central Processing Units (CPUs) or incorporating GPUs. ERF contains many of the standard discretizations and basic features needed to model general atmospheric dynamics as well as flows relevant to renewable energy. The modular design of ERF provides a flexible platform for exploring different physics parameterizations and numerical strategies. ERF is built on a state-of-the-art, well-supported, software framework (AMReX) that provides a performance portable interface and ensures ERF's long-term sustainability on next generation computing systems. This paper details the numerical methodology of ERF and presents results for a series of verification and validation cases.