High-Fidelity CFD in the Cloud – Thoughts and Perspectives

Speaker: Neil Ashton, Amazon Web Services
December 17, 2020

Presentation

Abstract

In this talk we’ll focus on exploring the motivation for using cloud computing for CFD from an industry and research viewpoint. Using examples from automotive, aerospace and manufacturing we’ll look at benchmarks for a number of CFD codes using CPUs (x86 & Arm) and GPUs and we’ll look at how the development of high-fidelity CFD e.g. WMLES, HRLES, is accelerating the need for access to large scale HPC. The onset of COVID-19 has also meant a large increase in the need for remote visualization with greater numbers of researchers and engineering needing to work from home. This has also accelerated the adoption of the same approaches needed towards the pre- and post-processing of peta/exa-scale CFD simulation and we’ll look at how these are more easily accessed via a cloud infrastructure. Finally, we’ll explore perspectives on integrating ML/AI into CFD workflows using data lakes from a range of sources and where the next decade may take us.

Biography

Neil Ashton is the Principal CFD Specialist at Amazon Web Services and a Visiting Fellow at the University of Oxford. Previous positions were at Lotus Formula 1 Team, University of Oxford as well as a visiting scholar at NASA Ames Research Canter in the LAVA Group. He has also had consultancy roles for Formula 1, Audi, British Cycling, Williams Advanced Engineering and others. His expertise is on applying and developing the next generation of Computational Fluid Dynamics approaches with a particular focus on interplay between high-fidelity turbulence models and High-Performance Computing (HPC). He was the chair of the Tenth International CFD conference, organiser of the 1st automotive CFD Prediction Workshop and more recently helping to coordinate the Hybrid RANS-LES working group of the 4th High-Lift Prediction Workshop.

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