By the same authors

Developing and Using a Geometric Multigrid, Unstructured Grid Mini-Application to Assess Many-Core Architectures

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Full text download(s)

Published copy (DOI)

Author(s)

  • Andrew Owenson
  • Steven Wright
  • Richard Bunt
  • Stephen Jarvis
  • Yoon Ho
  • Matthew Street

Department/unit(s)

Publication details

Title of host publicationProceedings - 26th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2018
DatePublished - 6 Jun 2018
Pages68-76
Number of pages9
PublisherInstitute of Electrical and Electronics Engineers Inc.
Original languageEnglish
ISBN (Electronic)9781538649756

Abstract

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.

Bibliographical note

© Copyright 2018 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

    Research areas

  • computational fluid dynamics, high performance computing, performance analysis, scientific computing

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations