A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model
文献类型：期刊论文
| 作者 | Huo, Zhijie3,4; Cleary, Matthew J. J.2,3; Wu, Kun4 ; Masri, Assaad R. R.3; Fan, Xuejun1,4; Fan XJ(范学军)
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| 刊名 | COMBUSTION THEORY AND MODELLING
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| 出版日期 | 2023-01-18 |
| 页码 | 29 |
| ISSN号 | 1364-7830 |
| 关键词 | dynamic load balancing DAC ISAT turbulent combustion MMC-LES |
| DOI | 10.1080/13647830.2023.2165967 |
| 通讯作者 | Wu, Kun(wukun@imech.ac.cn) |
| 英文摘要 | 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. |
| WOS关键词 | LARGE-EDDY SIMULATION ; MMC-LES ; DENSITY-FUNCTION ; FLAMES ; NUCLEATION |
| 资助项目 | National Key Project[GJXM92579] ; Australian Research Council[DP180104190] |
| WOS研究方向 | Thermodynamics ; Energy & Fuels ; Engineering ; Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000913612900001 |
| 资助机构 | National Key Project ; Australian Research Council |
| 源URL | [http://dspace.imech.ac.cn/handle/311007/91584]  |
| 专题 | 力学研究所_高温气体动力学国家重点实验室 |
| 通讯作者 | Wu, Kun |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Engn Sci, Beijing, Peoples R China 2.Univ Sydney, ARC ITTC Data Analyt Resources & Environm, Sydney, NSW, Australia 3.Univ Sydney, Sch Aerosp Mech & Mechatron Engn, Sydney, NSW, Australia 4.Chinese Acad Sci, Inst Mech, State Key Lab High Temp Gas Dynam, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Huo, Zhijie,Cleary, Matthew J. J.,Wu, Kun,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 | Huo, Zhijie,Cleary, Matthew J. J.,Wu, Kun,Masri, Assaad R. R.,Fan, Xuejun,&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 | Huo, Zhijie,et al."A dynamic load balancing model coupled with DAC and ISAT for a stochastic turbulent combustion model".COMBUSTION THEORY AND MODELLING (2023):29. |
入库方式： OAI收割
来源：力学研究所
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