Optimizing Load Balance in a Parallel CFD Code for a Large-scale Turbine Simulation on a Vector Supercomputer

被引:0
|
作者
Watanabe O. [1 ]
Komatsu K. [2 ]
Sato M. [2 ]
Kobayashi H. [2 ]
机构
[1] NEC Corporation, Tokyo
[2] Tohoku University, Sendai
关键词
hybrid parallelization; load balance; MPI; OpenMP; turbine simulation code; vector supercomputer;
D O I
10.14529/js210207
中图分类号
学科分类号
摘要
A turbine for power generation is one of the essential infrastructures in our society. A turbine’s failure causes severe social and economic impacts on our everyday life. Therefore, it is necessary to foresee such failures in advance. However, it is not easy to expect these failures from a real turbine. Hence, it is required to simulate various events occurring in the turbine by numerical simulations of the turbine. A multiphysics CFD code, “Numerical Turbine,” has been developed on vector supercomputer systems for large-scale simulations of unsteady wet steam flows inside a turbine. To solve this problem, the Numerical Turbine code is a block structure code using MPI parallelization, and the calculation space consists of grid blocks of different sizes. Therefore, load imbalance occurs when executing the code in MPI parallelization. This paper creates an estimation model that finds the calculation time from each grid block’s calculation amount and calculation performance. It proposes an OpenMP parallelization method for the load balance of MPI applications. This proposed method reduces the load imbalance by considering the vector performance according to the calculation amount based on the model. Moreover, this proposed method recognizes the need to reduce the load imbalance without pre-execution. The performance evaluation shows that the proposed method improves the load balance from 24.4 % to 9.3 %. © 2021. The Authors. All Rights Reserved.
引用
收藏
页码:114 / 130
页数:16
相关论文
共 50 条
  • [31] Semi-automatic porting of a large-scale Fortran CFD code to GPUs
    Corrigan, Andrew
    Camelli, Fernando
    Loehner, Rainald
    Mut, Fernando
    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, 2012, 69 (02) : 314 - 331
  • [32] Parallel workflow manager for non-parallel bioinformatic applications to solve large-scale biological problems on a supercomputer
    Suplatov, Dmitry
    Popova, Nina
    Zhumatiy, Sergey
    Voevodin, Vladimir
    Svedas, Vytas
    JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 2016, 14 (02)
  • [33] Parallel computing framework for optimizing construction planning in large-scale projects
    Kandil, A
    El-Rayes, K
    JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2005, 19 (03) : 304 - 312
  • [34] Influence of the vibration of large-scale wind turbine blade on the aerodynamic load
    Liu, Xiong
    Lu, Cheng
    Liang, Shi
    Godbole, Ajit
    Chen, Yan
    CLEAN, EFFICIENT AND AFFORDABLE ENERGY FOR A SUSTAINABLE FUTURE, 2015, 75 : 873 - 879
  • [36] A framework for reuse and parallelization of large-scale scientific simulation code
    Sherrill, ME
    Mancini, RC
    Harris, FC
    Dascalu, SM
    SERP '05: Proceedings of the 2005 International Conference on Software Engineering Research and Practice, Vols 1 and 2, 2005, : 52 - 58
  • [37] CFD simulation of large-scale bubble plumes: Comparisons against experiments
    Dhotre, Mahesh T.
    Smith, Brian L.
    CHEMICAL ENGINEERING SCIENCE, 2007, 62 (23) : 6615 - 6630
  • [38] A kinetic inlet model for CFD simulation of large-scale bubble columns
    Shi, Weibin
    Yang, Ning
    Yang, Xiaogang
    CHEMICAL ENGINEERING SCIENCE, 2017, 158 : 108 - 116
  • [39] Performance analysis of large scale parallel CFD computing based on Code_Saturne
    Shang, Zhi
    COMPUTER PHYSICS COMMUNICATIONS, 2013, 184 (02) : 381 - 386
  • [40] CFD simulation of homogenization in large-scale crude oil storage tanks
    Dakhel, AA
    Rahimi, M
    JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2004, 43 (3-4) : 151 - 161