Developing and using a geometric multigrid, unstructured grid mini-application to assess many-core architectures

Achieving high-performance of large scientific codes is a difficult task. This has led to the development of numerous mini-applications that are more tractable to analyse, while retaining performance characteristics of their full-sized counterparts. These “mini-apps” also enable faster hardware evaluation, and for sensitive codes allow evaluation of systems outside of access approval processes. In this paper we develop a mini-application of a geometric multigrid, unstructured grid Computational Fluid Dynamics (CFD) code, designed to exhibit similar performance characteristics without sharing code. We detail our experiences developing this application, using guidelines detailed in existing research, and contribute further additions to these to aid future mini-application developers. Our application is validated against the inviscid flux routine of HYDRA, a CFD code developed by Rolls-Royce, which confirms that the parent kernel and mini-application share fundamental causes of parallel inefficiency. We then use the mini-application to assess the impact of Intel's Knights Landing (KNL) on performance. We find that the mini-app and parent kernel continue to share scaling characteristics, however a comparison with Broadwell performance exposed significant differences between the kernels that were undetected by the validation