• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Yang Meifang, Che Yonggang, Gao Xiang. Heterogeneous Parallel Optimization of an Engine Combustion Simulation Application with the OpenMP 4.0 Standard[J]. Journal of Computer Research and Development, 2018, 55(2): 400-408. DOI: 10.7544/issn1000-1239.2018.20160872
Citation: Yang Meifang, Che Yonggang, Gao Xiang. Heterogeneous Parallel Optimization of an Engine Combustion Simulation Application with the OpenMP 4.0 Standard[J]. Journal of Computer Research and Development, 2018, 55(2): 400-408. DOI: 10.7544/issn1000-1239.2018.20160872

Heterogeneous Parallel Optimization of an Engine Combustion Simulation Application with the OpenMP 4.0 Standard

More Information
  • Published Date: January 31, 2018
  • LESAP is a combustion simulation application capable of simulating the chemical reactions and supersonic flows in the scramjet engines. It can be used to solve practical engineering problems and involve a large amount of computations. In this paper, we port and optimize LESAP with the OpenMP 4.0 accelerator model, targeting the heterogeneous many-core platform composed of general CPU and Intel Many Integrated Core (MIC). Based on the application characteristics, a series of techniques are proposed, including OpenMP 4.0 based task offloading, data movement optimization, grid-partition based load-balancing and SIMD optimization. The performance evaluation is done for a real combustion simulation configuration, with 5 320 896 grid cells, on one Tianhe-2 supercomputer node. The results show that the resulting heterogenous code significantly outperforms the original CPU only code. When the heterogenous code runs on two Intel Xeon E5-2692 CPUs and three Intel Xeon Phi 31S1P coprocessors, the runtime per time-steep is reduced from 64.72 seconds to 21.06 seconds. The heterogeneous computing achieves a speedup of 3.07 times over the original code that only runs on the two Intel Xeon E5-2692 CPUs.
  • Related Articles

    [1]Wang Chuang, Ding Yan, Huang Chenlin, Song Liantao. Bitsliced Optimization of SM4 Algorithm with the SIMD Instruction Set[J]. Journal of Computer Research and Development, 2024, 61(8): 2097-2109. DOI: 10.7544/issn1000-1239.202220531
    [2]Li Maowen, Qu Guoyuan, Wei Dazhou, Jia Haipeng. Performance Optimization of Neural Network Convolution Based on GPU Platform[J]. Journal of Computer Research and Development, 2022, 59(6): 1181-1191. DOI: 10.7544/issn1000-1239.20200985
    [3]Shen Jie, Long Biao, Jiang Hao, Huang Chun. Implementation and Optimization of Vector Trigonometric Functions on Phytium Processors[J]. Journal of Computer Research and Development, 2020, 57(12): 2610-2620. DOI: 10.7544/issn1000-1239.2020.20190721
    [4]Zhang Jun, Xie Jingcheng, Shen Fanfan, Tan Hai, Wang Lümeng, He Yanxiang. Performance Optimization of Cache Subsystem in General Purpose Graphics Processing Units: A Survey[J]. Journal of Computer Research and Development, 2020, 57(6): 1191-1207. DOI: 10.7544/issn1000-1239.2020.20200113
    [5]Sun Chang’ai, Wang Zhen, Pan Lin. Optimized Mutation Testing Techniques for WS-BPEL Programs[J]. Journal of Computer Research and Development, 2019, 56(4): 895-905. DOI: 10.7544/issn1000-1239.2019.20180037
    [6]Liu Song, Wu Weiguo, Zhao Bo, Jiang Qing. Loop Tiling for Optimization of Locality and Parallelism[J]. Journal of Computer Research and Development, 2015, 52(5): 1160-1176. DOI: 10.7544/issn1000-1239.2015.20131387
    [7]Wang Yongxian, Zhang Lilun, Che Yonggang, Xu Chuanfu, Liu Wei, Cheng Xinghua. Heterogeneous Computing and Optimization on Tianhe-2,Supercomputer System for High-Order Accurate CFD Applications[J]. Journal of Computer Research and Development, 2015, 52(4): 833-842. DOI: 10.7544/issn1000-1239.2015.20131922
    [8]Gu Rong, Yan Jinshuang, Yang Xiaoliang, Yuan Chunfeng, and Huang Yihua. Performance Optimization for Short Job Execution in Hadoop MapReduce[J]. Journal of Computer Research and Development, 2014, 51(6): 1270-1280.
    [9]Luo Hongbing, Zhang Xiaoxia, Wang Wei, and Wu Linping. Instruction Level Parallel Optimizing for Scientific Computing Application[J]. Journal of Computer Research and Development, 2014, 51(6): 1263-1269.
    [10]Li Lei, Niu Chunlei, Chen Ningjiang, Wei Jun. A High-Performance Strategy for Optimizing Web Services[J]. Journal of Computer Research and Development, 2007, 44(7): 1191-1198.
  • Cited by

    Periodical cited type(2)

    1. 喻高远,马志强,李俊杰,金先龙. 基于申威异构众核处理器架构的模态并行算法. 振动与冲击. 2022(03): 224-230 .
    2. 聂含伊,杨希,张文喆. 面向多领域的高性能计算机应用综述. 计算机工程与科学. 2018(S1): 145-153 .

    Other cited types(4)

Catalog

    Article views (1214) PDF downloads (459) Cited by(6)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return