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Predictive analysis of code optimisations on large-scale coupled CFD-combustion simulations using the CPX mini-app
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Powell, A. and Mudalige, Gihan R. (2023) Predictive analysis of code optimisations on large-scale coupled CFD-combustion simulations using the CPX mini-app. In: 37th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2023), St. Petersburg, Florida, USA, 15-19 May 2023. Published in: 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS) ISBN 9798350337662. doi:10.1109/IPDPS54959.2023.00064 ISSN 1530-2075.
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Official URL: https://doi.org/10.1109/IPDPS54959.2023.00064
Abstract
As the complexity of multi-physics simulations increases, there is a need for efficient flow of information between components. Discrete ‘coupler’ codes can abstract away this process, improving solver interoperability. One such multi-physics problem is modelling a gas turbine aero engine, where instances of rotor/stator CFD and combustion simulations are coupled. Allocating resources correctly and efficiently during production simulations is a significant challenge due to the large HPC resources required and the varying scalability of specific components, a result of differences between solver physics. In this research, we develop a coupled mini-app simulation and an accompanying performance model to help support this process. We integrate an existing Particle-In-Cell mini-app, SIMPIC, as a ‘performance proxy’ for production combustion codes in industry, into a coupled mini-app CFD simulation using the CPX mini-coupler. The bottlenecks of the workload are examined, and the performance behavior are replicated using the mini-app. A selection of optimizations are examined, allowing us to estimate the workload’s theoretical performance. The coupling of mini-apps is supported by an empirical performance model which is then used to load balance and predict the speedup of a full-scale compressor-combustor-turbine simulation of 1.2Bn cells, a production representative problem size. The model is validated on 40K-cores of an HPE-Cray EX system, predicting the runtime of the mini-app work-flow with over 75% accuracy. The developed coupled mini-apps and empirical model combination demonstrates how rapid design space and run-time setup exploration studies can be carried out to obtain the best performance from full-scale Combustion-CFD coupled simulations.
Item Type: | Conference Item (Paper) | ||||||||||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TA Engineering (General). Civil engineering (General) T Technology > TL Motor vehicles. Aeronautics. Astronautics |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||||||
Library of Congress Subject Headings (LCSH): | Computational fluid dynamics , Automobiles - Motors -- Combustion, High performance computing | ||||||||||||
Journal or Publication Title: | 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS) | ||||||||||||
Publisher: | IEEE Computer Society | ||||||||||||
ISBN: | 9798350337662 | ||||||||||||
ISSN: | 1530-2075 | ||||||||||||
Official Date: | 18 July 2023 | ||||||||||||
Dates: |
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DOI: | 10.1109/IPDPS54959.2023.00064 | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Re-use Statement: | © 2023 Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
Date of first compliant deposit: | 1 February 2023 | ||||||||||||
Date of first compliant Open Access: | 1 February 2023 | ||||||||||||
RIOXX Funder/Project Grant: |
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Conference Paper Type: | Paper | ||||||||||||
Title of Event: | 37th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2023) | ||||||||||||
Type of Event: | Other | ||||||||||||
Location of Event: | St. Petersburg, Florida, USA | ||||||||||||
Date(s) of Event: | 15-19 May 2023 | ||||||||||||
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