A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model

doi:10.1080/13647830.2023.2165967

	A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model
	Huo ZJ(霍志杰); Cleary, Matthew J J; Wu K(吴坤); Masri, Assaad R R; Fan XJ(范学军)
通讯作者	Wu, Kun(wukun@imech.ac.cn)
发表期刊	COMBUSTION THEORY AND MODELLING
	2023-01-18
页码	29
ISSN	1364-7830
摘要	Due to the composition-dependent stiffness of chemistry, simulations of reactive turbulent flows may present computational load imbalance among parallel processes when spatial decomposition is used for parallelisation, causing high CPU idle time and waste of computational resources. To increase computational efficiency, a dynamic load balancing (DLB) model is proposed to redistribute computational load among computing cores. The DLB model exploits a decomposition in the mixture fraction space with two dynamic adjusting decomposition strategies to realise load redistribution. The DLB model is suitable for the integration of chemistry on stochastic particles in hybrid Eulerian/Lagrangian turbulent combustion models in which the Eulerian field is conventionally decomposed statically in physical space in a way that balances the computational load for the solution of the Navier-Stokes equation but which does not generally lead to balanced load for the computation of the composition fields. Here it is tested using an OpenFOAM-based platform, mmcFoam, which is a comprehensive object-orientated C++ library for stochastic turbulent combustion modelling. Apart from direct integration (DI) for chemistry, the DLB model is also coupled with dynamic adaptive chemistry (DAC) and in situ adaptive tabulation (ISAT), which allows for extra speedup. The performance of the coupled models is validated and assessed for two laboratory flame conditions that exhibit different levels of computational load imbalance. Overall, the DLB model effectively balances the computational load distribution and increases the effective usage of computing power, shortening the simulation wall time required. Moreover, a strong scaling test is carried out using up to 512 cores. Although all approaches have sub-ideal scalability, the scalability of each with DLB is significantly better than without DLB. While DLB-ISAT has relatively poor scalability compared to the DI- and DAC-based methods, DLB-ISAT still ranks the fastest among the algorithms in all scaling trials.
关键词	dynamic load balancing DAC ISAT turbulent combustion MMC-LES
DOI	10.1080/13647830.2023.2165967
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000913612900001
关键词[WOS]	LARGE-EDDY SIMULATION ; MMC-LES ; DENSITY-FUNCTION ; FLAMES ; NUCLEATION
WOS研究方向	Thermodynamics ; Energy & Fuels ; Engineering ; Mathematics
WOS类目	Thermodynamics ; Energy & Fuels ; Engineering, Chemical ; Mathematics, Interdisciplinary Applications
资助项目	National Key Project[GJXM92579] ; Australian Research Council[DP180104190]
项目资助者	National Key Project ; Australian Research Council
论文分区	Q3
力学所作者排名	1
RpAuthor	Wu, Kun
引用统计
文献类型	期刊论文
条目标识符	http://dspace.imech.ac.cn/handle/311007/91585
专题	高温气体动力学国家重点实验室
推荐引用方式 GB/T 7714	Huo ZJ,Cleary, Matthew J J,Wu K,et al. A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model[J]. COMBUSTION THEORY AND MODELLING,2023:29.
APA	霍志杰,Cleary, Matthew J J,吴坤,Masri, Assaad R R,&范学军.(2023).A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model.COMBUSTION THEORY AND MODELLING,29.
MLA	霍志杰,et al."A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model".COMBUSTION THEORY AND MODELLING (2023):29.

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