Advanced Search

Indexed by SCI、CA、РЖ、PA、CSA、ZR、etc .

Volume 30 Issue 4
Aug 2019
Turn off MathJax
Article Contents
Wenge Liu, Fan Wang, Huawei Zhou. Parallel Seismic Modeling Based on OpenMP+AVX and Optimization Strategy. Journal of Earth Science, 2019, 30(4): 843-848. doi: 10.1007/s12583-018-0831-3
Citation: Wenge Liu, Fan Wang, Huawei Zhou. Parallel Seismic Modeling Based on OpenMP+AVX and Optimization Strategy. Journal of Earth Science, 2019, 30(4): 843-848. doi: 10.1007/s12583-018-0831-3

Parallel Seismic Modeling Based on OpenMP+AVX and Optimization Strategy

doi: 10.1007/s12583-018-0831-3
Funds:

the National Science and Technology Major Projects of China 2017ZX05035003-001

the National Natural Science Foundation of China 41274140

More Information
  • Corresponding author: Wenge Liu
  • Received Date: 27 Sep 2016
  • Accepted Date: 15 Apr 2017
  • Publish Date: 01 Aug 2019
  • This paper describes parallel simulation of the memory/computation-intensive acoustic wave equation with CPU template buffer optimization. Considering the 8-core CPU shared storage platform as an example, we obtain a one-time speed-up ratio of 6.7×compared with the serial program by using a coarse-grained OpenMP parallel scheme. Then, data is vectorized on the template buffer using the single instruction-multiple data (SIMD) technique to further exploit the computing potential of the CPUs. We apply an 8-channel parallel vector to simulate seismic wavefields with the 256-bit advanced vector extensions (AVX) instruction set. This increases the computing bandwidth, thus eliminating a significant volume of the computing instructions and obtaining a secondary speed-up ratio of 3-7×. In addition, we use 32-byte data alignment, shortest data direction vectorization, and loop tiling optimization algorithm to achieve faster program execution. Finally, we analyze the factors affecting the secondary speed-up of AVX through three-dimensional modeling experiments with the salt model. The results indicate that the memory, cache, and register can better cooperate with each other and the speed-up is increased by optimizing the AVX algorithm.

     

  • loading
  • Agulleiro, J. I., Fernandez, J. J., 2015. Tuning the Cache Memory Usage in Tomographic Reconstruction on Standard Computers with Advanced Vector Extensions (AVX). Data in Brief, 3:16-20. https://doi.org/10.1016/j.dib.2014.12.010
    Bian, A. F., Zou, Z. H., Zhou, H. W., et al., 2015. Evaluation of Multi-Scale Full Waveform Inversion with Marine Vertical Cable Data. Journal of Earth Science, 26(4):481-486. https://doi.org/10.1007/s12583-015-0566-3
    Calandra, H., Bothorel, F., Vezolle, P., 2008. A Massively Parallel Imple-mentation of the Common Azimuth Pre-Stack Depth Migration. IBM Journal of Research and Development, 52(1/2):83-91. https://doi.org/10.1147/rd.521.0083
    Etgen, J. T., O'Brien, M. J., 2007. Computational Methods for Large-Scale 3D Acoustic Finite-Difference Modeling:A Tutorial. Geophysics, 72(5):SM223-SM230. https://doi.org/10.1190/1.2753753
    Francés, J., Bleda, S., Márquez, A., et al., 2014. Performance Analysis of SSE and AVX Instructions in Multi-Core CPUs and GPU Computing on FDTD Scheme for Solid and Fluid Vibration Problems. The Journal of Supercomputing, 70(2):514-526. https://doi.org/10.1007/s11227-013-1065-x
    Gregory, K., Miller, A., 2012. C++ AMP:Accelerated Massive Parallelism with Micorsoft Visual C++. Microsoft Press, Redmond. 127-170
    Gokhberg, A., Fichtner, A., 2016. Full-Waveform Inversion on Heterogene-ous HPC Systems. Computers & Geosciences, 89:260-268. https://doi.org/10.13039/501100003246
    Huang, W., Zhou, H. W., 2015. Least-Squares Seismic Inversion with Stochastic Conjugate Gradient Method. Journal of Earth Science, 26(4):463-470. https://doi.org/10.1007/s12583-015-0553-8
    Jayaseelan, R., Liu, H., Mitra, T., 2006. Exploiting Forwarding to Improve Data Bandwidth of Instruction-Set Extensions. 2006 43rd ACM/IEEE Design Automation Conference, July 24-28, San Francisco
    Mojica, O. F., Bassrei, A., 2015. Generalized Cross-Validation and Regín-ska's Methods for Choosing the Regularization Parameter in 3D Gravity Inversion of Basement Relief-A Hybrid MPI/OpenMP Parallel Algorithm. 14th International Congress of the Brazilian Geophysical Society & Expogef, August 3-6, Rio de Janeiro
    Ronn, F., 2003. Cache-Oblivious Searching and Sorting: [Dissertation]. University of Copenhagen, Copenhagen. 7-36
    Souza, P., Borges, L., Andreolli, C., et al., 2015. OpenVec Portable SIMD Intrinsics. Second EAGE Workshop on High Performance Computing for Upstream, September 13-16, Dubai
    Stock, K. A., 2014, Vectorization and Register Reuse in High Performance Computing: [Dissertation]. The Ohio State University, Columbus. 16-21
    Zhang, L. Z., Du, Y. X., Wu, D. C., 2015. GPU-Accelerated FDTD Simulation of Human Tissue Using C++ AMP. The 31st Annual Review of Progress in Applied Computational Electromagnetics, March 22-26, Williamsburg
    Zhou, M. H., Symes, W. W., 2014. Wave Equation Based Stencil Optimizations on Multi-Core CPU. 2014 SEG Annual Meeting, October 26-31, Denver
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(7)

    Article Metrics

    Article views(409) PDF downloads(16) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return