Load balance and parallel I/O: Optimising COSA for large simulations
Load balance and parallel I/O: Optimising COSA for large simulations
This paper presents the optimisation of the parallel functionalities of the Navier-Stokes Computational Fluid Dynamics research code COSA, a finite volume structured multi-block code featuring a steady solver, a general purpose time-domain solver, and a frequency-domain harmonic balance solver for the rapid solution of unsteady periodic flows. The optimisation focuses on improving the scalability of the parallel input/output functionalities of the code and developing an effective and user-friendly load balancing approach. Both features are paramount for using COSA efficiently for large-scale production simulations using tens of thousands of computational cores. The efficiency enhancements resulting from optimising the parallel I/O functionality and addressing load balance issues has provided up to a 4× performance improvement for unbalanced simulations, and 2× performance improvements for balanced simulations.
COSA, Decomposition, I/O, Load balance, Optimisation, Parallel performance
Jackson, Adrian
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Campobasso, M. Sergio
ccc82d53-2d65-42bc-b46a-1ba5020b32c7
Drofelnik, Jernej
e785f695-61ef-4afc-bf0a-9dc7966f5516
Jackson, Adrian
8173ef36-a41f-4573-b54a-f37e46c56bb9
Campobasso, M. Sergio
ccc82d53-2d65-42bc-b46a-1ba5020b32c7
Drofelnik, Jernej
e785f695-61ef-4afc-bf0a-9dc7966f5516
Jackson, Adrian, Campobasso, M. Sergio and Drofelnik, Jernej
(2018)
Load balance and parallel I/O: Optimising COSA for large simulations.
Computers & Fluids.
(doi:10.1016/j.compfluid.2018.03.007).
Abstract
This paper presents the optimisation of the parallel functionalities of the Navier-Stokes Computational Fluid Dynamics research code COSA, a finite volume structured multi-block code featuring a steady solver, a general purpose time-domain solver, and a frequency-domain harmonic balance solver for the rapid solution of unsteady periodic flows. The optimisation focuses on improving the scalability of the parallel input/output functionalities of the code and developing an effective and user-friendly load balancing approach. Both features are paramount for using COSA efficiently for large-scale production simulations using tens of thousands of computational cores. The efficiency enhancements resulting from optimising the parallel I/O functionality and addressing load balance issues has provided up to a 4× performance improvement for unbalanced simulations, and 2× performance improvements for balanced simulations.
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More information
Accepted/In Press date: 1 March 2018
e-pub ahead of print date: 5 March 2018
Keywords:
COSA, Decomposition, I/O, Load balance, Optimisation, Parallel performance
Identifiers
Local EPrints ID: 421609
URI: http://eprints.soton.ac.uk/id/eprint/421609
ISSN: 0045-7930
PURE UUID: ba4f1792-8c77-403d-aa76-3ea3eb9180ae
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Date deposited: 15 Jun 2018 16:31
Last modified: 05 Jun 2024 18:40
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Contributors
Author:
Adrian Jackson
Author:
M. Sergio Campobasso
Author:
Jernej Drofelnik
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