Accelerating finite difference wavefield-continuation depth migration by GPU

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#KD-D.N&I/s;v,i:RC0Accelerating finite difference wavefield-continuation depth migration by GPU水利论文AY$^x|G

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v(N"U2^.i:n;CnI0Abstract:水利论文"Z"sL ~o4]KR [-E

1\,zOn#cY0The 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 finite 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.

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Liu Guo-Feng[1]水利论文'}1Yq.|Y'Qv0c

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Meng Xiao-Hong[1]水利论文n x%e$h1Qa%AHu

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Liu Hong[2]水利论文H gq5F+Ws wf

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,EbX&]CAR5S%Z{0Key Laboratory of Geo-detection(China University of Geosciences, Beijing), Ministry of Education, Beijing 100083, China水利论文SHl/E_DiwL

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Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China水利论文L+z7Vq1~ j6iX9v

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Applied Geophysics水利论文O W A uoG EL:]

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^%l9m!BdXX0Keywords:

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Wavefield-continuation depth migration水利论文;h3c:w.PD_~4U?'x

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finite difference

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Graphic Processing Unit

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Accelerating finite difference wavefield-continuation depth migration by GPU

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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 ha...水利论文 c%zu~(Sf

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