Computer Science ›› 2022, Vol. 49 ›› Issue (10): 66-73.doi: 10.11896/jsjkx.220100089

• High Perfonnance Computing • Previous Articles     Next Articles

Parallel Optimization of Computational Fluid Dynamics Application Palabos Based on NextGeneration Sunway Supercomputer

LIU An-jun1, YIN Hong-hui2, WANG Li1, LIU Zhi-xiang3, KONG Bo4, GUO Meng1,2, CHEN Cheng-min2, YANG Mei-hong1   

  1. 1 Shandong Computer Science Center(National Supercomputing Center in Jinan),Qilu University of Technology(Shandong Academy of Sciences),Jinan 250014,China
    2 Jinan Key Laboratory of High Performance Industrial Software,Jinan Institute of Supercomputer Technology,Jinan 251013,China
    3 College of Information Technology,Shanghai Ocean University,Shanghai 201306,China
    4 Guangdong Technion Israel Institute of Technology,Shantou,Guangdong 526100,China
  • Received:2022-01-10 Revised:2022-05-09 Online:2022-10-15 Published:2022-10-13
  • About author:LIU An-jun,born in 1990,Ph.D.His main research interests include parallel computing and mass/momentum/heat transfer.
    YANG Mei-hong,born in 1966,postgraduate,professor,Ph.D,supervisor.Her main research interests include cloud computing,big data and software engineering.
  • Supported by:
    National Key Research and Development Program(2018YFB0704002),Aoshan Science and Technology Innovation Project(2018ASKJ01), Major Scientific and Technological Innovation Projects in Shandong Province(2019JZZY010302),Shandong Key Research and Development Program(International Cooperation Office)(2019GHZ018),Shandong Province Postdoctoral Innovative Talents Support Plan(SDBX2020018) and GH fund B(202107021062).

Abstract: Parallel lattice Boltzmann(Palabos)software is a widely used computational fluid dynamics software based on lattice Boltzmann method(LBM),which is widely used in the field of porous media,free interface,particle motion,blood flow and so on due to its excellent computing power.Palabos has a wide range of user needs,which makes it urgent to transplant,optimize and accelerate parallel on Sunway supercomputer to serve the energy and chemical industry.In this paper,the heterogeneous parallel design of Palabos software is carried out on the new generation Sunway supercomputer system(SW26010pro).The data structure and template programming of Palabos are not suitable for the heterogeneous parallel of Sunway supercomputer system.So we design the parallel optimization techniques called direct getting address,polymorphic tag processing and data slicing to deal with the Palabos data structure and template programming.Combined with the characteristics of the new generation of Sunway supercomputer system,the optimization technology of shared memory and register memory access(RMA) is also adopted.The acceleration efficiency of 64 computing processing elements(CPEs) is 2~6 speed up.The Palabos software is realized the parallel computing of one million core scale of two-phase flow algorithm in the field of complex multi-scale chemical process in the new generation Sunway supercomputer system.The one million cores parallel efficiency is more than 40% compared with 64 000 cores.

Key words: Many core, Modulation programming, Palabos, SW26010pro, Multiphase flow

CLC Number: 

  • TP391
[1]LV X J,LIU Z,CHU X S,et al.Extreme-scale simulation based LBM computing fluid dynamics simulations[J].Computer Science,2020,47(4):13-17.
[2]LIU Z,CHU X S,LV X J,et al.SunWayLB:Enabling extreme-scale Lattice Boltzmann Method based computing fluid dynamics simulations on Sunway TaihuLight[C]//2019 IEEE International Parallel and Distributed Processing Symposium(IPDPS).IEEE Computer Society,2019:557-566.
[3]LIU Z X,FANG Y,SONG A P,et al.Large-Scale scalable parallel computing based on LBM with multiple-relaxation-time model[J].Journal of Computer Research and Development,2016,53(5):1156-1165.
[4]TIAN M,GU W,PAN J,et al.In Performance analysis and optimization of palabos on petascale sunway BlueLight MPP supercomputer[C]//International Conference on Parallel Computing in Fluid Dynamics.Springer,2013:311-320.
[5]OBRECHT C,KUZNIK F,TOURANCHEAU B,et al.TheTheLMA project:a thermal lattice Boltzmann solver for the GPU [J/OL].Computers & Fluids,2014,54:118-126.https://doi.org/10.1016/j.compfluid.2011.10.011.
[6]YE H,SHEN Z,XIAN W,et al.OpenFSI:A highly efficient and portable fluid-structure simulation package based on immersed-boundary method[J/OL].Computer Physics Communications,2020:107463.https://doi.org/10.1016/j.cpc.2020.107463.
[7]BONACCORSO F,MONTESSORI A,TIRIBOCCHI A,et al.LBsoft:a parallel open-source software for simulation of colloidal systems[J/OL].Computer Physics Communications,2020:107455.https://doi.org/10.1016/j.procs.2017.05.084.
[8]ZAVODSZKY G,VAN ROOIJ B,AZIZI V,et al.Hemocell:ahigh-performance microscopic cellular library[J/OL].Procedia Computer Science,2017,108:159-165.https://doi.org/10.1016/j.procs.2017.05.084.
[9]HASERT M,MASILAMANI K,ZIMNY S,et al.Complex fluid simulations with the parallel tree-based lattice Boltzmann solver Musubi[J].Journal of Computational Science,2014,5 (5):784-794.
[10]LATT J,MALASPINAS O,KONTAXAKIS D,et al.Palabos:Parallel Lattice Boltzmann Solver[J].Computers & Mathema-tics with Applications,2021,81(1):334-350.
[11]LATT J,CHOPARD B.VLADYMIR—a C++ matrix library for data-parallel applications[J].Future Generation Computer Systems,2004,20(6):1023-1039.
[12]MOHAMMADREZAEI S,SIAVASHI M,ASIAEI S.Surfacetopography effects on dynamic behavior of water droplet over a micro-structured surface using an improved-VOF based lattice Boltzmann method[J/OL].Journal of Molecular Liquids,2022:118509.https://doi.org/10.1016/j.molliq.2022.118509.
[13]XIA T,FENG Q,WANG S,et al.A numerical study of particle migration in porous media during produced water reinjection[J/OL].Journal of Energy Resources Technology,2022,144 (7):073002.https://doi.org/10.1115/1.4052165.
[14]ZAVODSZKY G,VAN ROOIJ B,CZAJA B,et al.Red bloodcell and platelet diffusivity and margination in the presence of cross-stream gradients in blood flows[J/OL].Physics of Fluids,2019,31(3):031093.https://doi.org/10.1063/1.5085881.
[15]KOTSALOS C,LATT J,CHOPARD B.Bridging the computational gap between mesoscopic and continuum modeling of red blood cells for fully resolved blood flow[J/OL].Journal of Computational Physics,2019,398:108905.https://doi.org/10.1016/j.jcp.2019.108905.
[16]KOTSALOS C,LATT J,BENY J,et al.Digital blood in mas-sively parallel CPU/GPU systems for the study of platelet transport[J/OL].Interface Focus:a Theme Supplement of Journal of the Royal Society Interface,2021,11(1):20190116.https://doi.org/10.1098/rsfs.2019.0116.
[17]BOUDJELTIA K Z,KOTSALOS C,DRIBEIRO D,et al.Spherization of red blood cells and platelet margination in COPD patients[J].Annals of the New York Academy of Sciences,2021,1485(1):71-82.
[18]LIU Y,LIU X,LI F,et al.In Closing the “quantum supremacy” gap:achieving real-time simulation of a random quantum circuit using a new Sunway supercomputer[C/OL]//Proceedings of the International Conference for High Performance Computing,Networking,Storage and Analysis.IEEE Computer Society,2021.https://doi.org/10.48550/arXiv.2110.14502.
[19]XIAO J,CHEN J,ZHENG J,et al.In Symplectic structure-preserving particle-in-cell whole-volume simulation of tokamak plasmas to 111.3 trillion particles and 25.7 billion grids[C/OL]//Proceedings of the International Conference for High Perfor-mance Computing,Networking,Storage and Analysis.IEEE Computer Society,2021.https://doi.org/10.1145/3458817.3487398.
[20]SHANG H,LI F,ZHANG Y,et al.In Extreme-scale ab initio quantum raman spectra simulations on the leadership HPC system in China[C/OL]//Proceedings of the International Confe-rence for High Performance Computing,Networking,Storage and Analysis.IEEE Computer Society,2021.https://doi.org/10.1145/3458817.3487402.
[1] WANG Lu-han, JIA Hai-peng, ZHANG Yun-quan, ZHANG Guang-ting. Study on Implementation and Optimization of ARM-based Image Geometric Transformation Library [J]. Computer Science, 2022, 49(10): 10-17.
[2] LI Zhi-ying, MA Shuo, ZHOU Chao, MA Ying-jin, LIU Qian, JIN Zhong. “AI+HPC”-based Time Prediction for the First Principle Calculations and Its Applications in Biomed Community [J]. Computer Science, 2022, 49(10): 36-43.
[3] CHEN Zhi-yu, SHAN Zhi-long. Research Advances in Knowledge Tracing [J]. Computer Science, 2022, 49(10): 83-95.
[4] LIU Meng-xin, ZHANG Fan, LI Tian-rui. Edge Bundling Method Based on Homologous Control Points [J]. Computer Science, 2022, 49(10): 96-102.
[5] LIU Yang, ZHENG Wen-ping, ZHANG Chuan, WANG Wen-jian. Local Random Walk Based Label Propagation Algorithm [J]. Computer Science, 2022, 49(10): 103-110.
[6] CHEN Kai, LIU Man, WANG Zhi-teng, MAO Shao-chen, SHEN Qiu-hui, ZHANG Hong-jun. Study on Data Filling Based on Global-attributes Attention Neural Process Model [J]. Computer Science, 2022, 49(10): 111-117.
[7] REN Sheng-lan, GUO Hui-juan, HUANG Wen-hao, TANG Zhi-hong, Qi Hui. Recommendation Method Based on Attention Mechanism Interactive Convolutional Neural Network [J]. Computer Science, 2022, 49(10): 126-131.
[8] ZHANG Min, YU Zeng, HAN Yun-xing, LI Tian-rui. Overview of Person Re-identification for Complex Scenes [J]. Computer Science, 2022, 49(10): 138-150.
[9] MIAO Zhuang, WANG Ya-peng, LI Yang, WANG Jia-bao, ZHANG Rui, ZHAO Xin-xin. Robust Hash Learning Method Based on Dual-teacher Self-supervised Distillation [J]. Computer Science, 2022, 49(10): 159-168.
[10] HUANG Zhong-hao, YANG Xing-yao, YU Jiong, GUO Liang, LI Xiang. Mutual Learning Knowledge Distillation Based on Multi-stage Multi-generative Adversarial Network [J]. Computer Science, 2022, 49(10): 169-175.
[11] LU Ping, ZHANG Di, XIAO Jun-feng, BI Ke. Study on 3D Motion-in-Depth Perception Based on Binocular Vision [J]. Computer Science, 2022, 49(10): 176-182.
[12] ZHANG Fu-chang, ZHONG Guo-qiang, MAO Yu-xu. Neural Architecture Search for Light-weight Medical Image Segmentation Network [J]. Computer Science, 2022, 49(10): 183-190.
[13] PAN Yi, WANG Li-ping. Object Detection Algorithm Based on Improved Split-attention Network [J]. Computer Science, 2022, 49(10): 198-206.
[14] LIU Na-li, TIAN Yan, SONG Ya-dong, JIANG Teng-fei, WANG Xun, YANG Bai-lin. Voxel Deformation Network Based on Environmental Information Mining [J]. Computer Science, 2022, 49(10): 207-213.
[15] FENG Jun, WEI Da-bao, SU Dong, HANG Ting-ting, LU Jia-min. Survey of Document-level Entity Relation Extraction Methods [J]. Computer Science, 2022, 49(10): 224-242.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!