A highly scalable Met Office NERC Cloud model

TL;DR

This paper introduces MONC, a re-engineered, highly scalable Large Eddy Simulation model for atmospheric research, designed to leverage modern high-performance computing architectures and improve upon the original LEM's scalability limitations.

Contribution

The paper presents MONC, a redesigned, extensible LES model that significantly improves scalability and performance on large HPC systems compared to the original LEM.

Findings

MONC scales efficiently beyond 512 cores.

Enhanced performance at large core counts.

Provides new scientific modeling capabilities.

Abstract

Large Eddy Simulation is a critical modelling tool for scientists investigating atmospheric flows, turbulence and cloud microphysics. Within the UK, the principal LES model used by the atmospheric research community is the Met Office Large Eddy Model (LEM). The LEM was originally developed in the late 1980s using computational techniques and assumptions of the time, which means that the it does not scale beyond 512 cores. In this paper we present the Met Office NERC Cloud model, MONC, which is a re-write of the existing LEM. We discuss the software engineering and architectural decisions made in order to develop a flexible, extensible model which the community can easily customise for their own needs. The scalability of MONC is evaluated, along with numerous additional customisations made to further improve performance at large core counts. The result of this work is a model which delivers to the community significant new scientific modelling capability that takes advantage of the current and future generation HPC machines.