지구물리와물리탐사 (Geophysics and Geophysical Exploration)

  • 제19권3호
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  • Pages.145-152
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  • 2016
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  • 1229-1064(pISSN)
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  • 2384-051X(eISSN)
한국지구물리·물리탐사학회 (Korean Society of Earth and Exploration Geophysicists)
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그래픽 프로세서를 이용한 시간 영역 3차원 파동 전파 모델링과 메모리 관리

Time-domain 3D Wave Propagation Modeling and Memory Management Using Graphics Processing Units

  • 김아름 (부경대학교 에너지자원공학과) ;
  • 류동현 (부경대학교 에너지자원공학과) ;
  • 하완수 (부경대학교 에너지자원공학과)
  • Kim, Ahreum (Department of Energy Resources Engineering, Pukyong National University) ;
  • Ryu, Donghyun (Department of Energy Resources Engineering, Pukyong National University) ;
  • Ha, Wansoo (Department of Energy Resources Engineering, Pukyong National University)
  • 투고 : 2016.08.02
  • 심사 : 2016.08.18
  • 발행 : 2016.08.31
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초록

효율적인 시간 영역 3차원 파동 전파 모델링을 위해 그래픽 프로세서를 사용하였다. 그래픽 프로세서는 대규모 병렬 연산을 위한 프로세서로, 그래픽 프로세서를 효율적으로 이용하기 위해서는 계산 과정과 메모리 복사 과정을 최적화할 필요가 있다. 본 연구에서는 메모리 관리에 초점을 맞추고 메모리 관리 방법에 따라 그래픽 프로세서를 이용한 프로그램의 성능이 어떻게 달라지는지 확인하였다. 또한 유한 차분법 차수와 속도 모델의 크기를 변화시켜가며 메모리 복사가 프로그램 성능에 미치는 영향을 시험하였다. 그 결과 3차원 파동장 전체를 복사하는 프로그램에서 메모리 관리가 유한 차분법 계산보다 큰 비중을 차지함을 알 수 있었다.

We used graphics processing units for an efficient time-domain 3D wave propagation modeling. Since graphics processing units are designed for massively parallel processes, we need to optimize the calculation and memory management to fully exploit graphics processing units. We focused on the memory management and examined the performance of programs with respect to the memory management methods. We also tested the effects of memory transfer on the performance of the program by varying the order of finite difference equation and the size of velocity models. The results show that the memory transfer takes a larger portion of the running time than that of the finite difference calculation in programs transferring whole 3D wavefield.

키워드

참고문헌

  1. Aminzadeh, F., Burkhard, N., Nicoletis, L., Rocca, F., and Wyatt, K., 1994, SEG/EAEG 3-D modeling project: 2nd update, The Leading Edge, 13, 949-952. https://doi.org/10.1190/1.1437054
  2. Cheng, J., Grossman, M., and McKercher, T., 2014, Professional CUDA C programming, Wrox.
  3. CUDA Toolkit Documentation, 2016.8.1., http://docs.nvidia.com/cuda/
  4. Kim, Y., Y. Cho, U. Jang, and C. Shin, 2013, Acceleration of stable TTI P-wave reverse-time migration with GPUs, Computers and Geosciences, 52, 204-217. https://doi.org/10.1016/j.cageo.2012.10.013
  5. Kirk, D.B., and Hwu, W.W., 2013, Programming massively parallel processors, 2nd ed., Morgan Kaufmann.
  6. Komatitsch, D., D. Michea, and G. Erlebacher, 2009, Porting a high-order finite-element earthquake modeling application to NVIDIA graphics cards using CUDA, J. Parallel Distrib. Comput., 69, 451-460. https://doi.org/10.1016/j.jpdc.2009.01.006
  7. Komatitsch, D., G. Erlebacher, D. Goddeke, and D. Michea, 2010a, High-order finite-element seismic wave propagation modeling with MPI on a large GPU cluster, Journal of Computational Physics, 229, 7692-7714. https://doi.org/10.1016/j.jcp.2010.06.024
  8. Komatitsch, D., D. Goddeke, G. Erlebacher, and D. Michea, 2010b, Modeling the propagation of elastic waves using spectral elements on a cluster of 192 GPUs, Computer Science- Research and Development, 25, 75-82. https://doi.org/10.1007/s00450-010-0109-1
  9. Kreyszig, E., 2011, Advanced engineering mathematics, 10th Ed., John Wiley & Sons, Inc.
  10. Liu, G., Y. Liu, L. Ren, and X. Meng, 2013, 3D seismic reverse time migration on GPGPU, Computers and Geosciences, 59, 17-23. https://doi.org/10.1016/j.cageo.2013.05.009
  11. Michea, D., and D. Komatitsch, 2010, Accelerating a threedimensional finite-difference wave propagation code using GPU graphics cards, Geophysical Journal International, 182, 389-402.
  12. Micikevicius, P., 2009, 3D finite difference computation on GPUs using CUDA, Proceedings of 2nd Workshop on General Purpose GPU.
  13. Mu, D., P. Chen, and L. Wang, 2013, Accelerating the discontinuous Galerkin method for seismic wave propagation simulations using multiple GPUs with CUDA and MPI, Earthquake Science, 26, 377-393. https://doi.org/10.1007/s11589-013-0047-7
  14. Shi, X., C. Li, S. Wang, and X. Wang, 2010, Computing prestack Kirchhoff time migration on general purpose GPU, Computers and Geosciences, 37, 1702-1710.
  15. Shin, J., W. Ha, H. Jun, D.-J. Min, and C. Shin, 2014, 3D Laplace-domain full waveform inversion using a single GPU card, Computers and Geosciences, 67, 1-13. https://doi.org/10.1016/j.cageo.2014.02.006
  16. Suh, S., and B. Wang, 2011, Expanding domain methods in GPU based TTI reverse time migration, SEG Expanded Abstract Technical Program, 3460-3464.
  17. Wang, S.-Q., X. Gao, and Z.-X. Yao, 2010, Accelerating POCS interpolation of 3D irregular seismic data with Graphics Processing Units, Computers and Geosciences, 36, 1292-1300. https://doi.org/10.1016/j.cageo.2010.03.012
  18. Weiss, R. M., and J. Shragge, 2013, Solving 3D anisotropic elastic wave equations on parallel GPU devices, Geophysics, 78, F7-F15. https://doi.org/10.1190/geo2012-0063.1
  19. Yang, P., J. Gao, and B. Wang, 2014, RTM using effective boundary saving: A staggered grid GPU implementation, Computers and Geosciences, 68, 64-72. https://doi.org/10.1016/j.cageo.2014.04.004
  20. Yang, P., J. Gao, and B. Wang, 2015, A graphics processing unit implementation of time-domain full-waveform inversion, Geophysics, 80, F31-F39. https://doi.org/10.1190/geo2014-0283.1