Accelerating finite difference wavefi eld-continuation depth migration by GPU*
Liu Guo-Feng1，2, Meng Xiao-Hong1, and Liu Hong2
1. Key Laboratory of Geo-detection (China University of Geosciences, Beijing), Ministry of Education, Beijing 100083, China.
2. Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China.
Abstract The most popular hardware used for parallel depth migration is the PC-Cluster but its application is limited due to large space occupation and high power consumption. In this paper, we introduce a new hardware architecture, based on which the fi nite difference (FD) wavefield-continuation depth migration can be conducted using the Graphics Processing Unit (GPU) as a CPU coprocessor. We demonstrate the program module and three key optimization steps for implementing FD depth migration: memory, thread structure, and instruction optimizations and consider evaluation methods for the amount of optimization. 2D and 3D models are used to test depth migration on the GPU. The tested results show that the depth migration computational efficiency greatly increased using the general-purpose GPU, increasing by at least 25 times compared to the AMD 2.5 GHz CPU.
This work is supported by the National Natural Science Foundation of China (Nos. 41104083 and 40804024) and the Fundamental Research Funds for the Central Universities (No, 2011YYL022).
About author: Liu Guo-Feng: See biography and photo in the Applied Geophysics June 2009 issue, P. 137.
Email: liugf@cugb.edu.cn
Cite this article:
LIU Guo-Feng,MENG Xiao-Hong,LIU Hong. Accelerating finite difference wavefi eld-continuation depth migration by GPU*[J]. APPLIED GEOPHYSICS, 2012, 9(1): 41-48.
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