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A parallel computing method for Kirchhoff-like offsets on multiple GPUs

A parallel computing and offset technology, applied in the field of information processing, can solve the problems that the advantages of GPU many cores cannot be fully utilized, the GPU memory capacity is small, and the calculation efficiency is not high, so as to achieve less offset, increase calculation efficiency, and increase imaging effect of points

Active Publication Date: 2019-03-29
BEIJING GEOSTAR SCI & TECH
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Problems solved by technology

[0007] In order to solve the problem that the existing Kirchhoff-type offset algorithm based on GPU parallel computing has low calculation efficiency due to the small GPU memory capacity, and the GPU’s many-core advantages cannot be fully utilized. According to the calculation principle of Kirchhoff-type offset, the present invention provides A Kirchhoff-like offset parallel computing method on multi-GPU

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  • A parallel computing method for Kirchhoff-like offsets on multiple GPUs
  • A parallel computing method for Kirchhoff-like offsets on multiple GPUs
  • A parallel computing method for Kirchhoff-like offsets on multiple GPUs

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Embodiment 1

[0028] According to the method of the present invention, we use the data to test, the test GPU is GTX680, and the main frequency of CPU is 2.5GHz. Test results such as Figure 4 and Figure 5 Shown: Among them, the abscissa represents the number of imaging points, Figure 4 The ordinate of represents the computing time, the oblique line is the CPU computing time, and the horizontal line is the GPU computing time, it can be seen that the larger the data imaging space, the greater the acceleration of the GPU; Figure 5 Represents the ratio of CPU and GPU computing time, we can see that the larger the imaging space, the greater the speedup ratio. Figure 6 Is the CPU calculation and the comparison of the calculation results of the method of the present invention, wherein Figure 6 (a) is the CPU calculation result, Figure 6 (b) is the GPU calculation result, Figure 6 (c) is a single-channel comparison between the two. From Figure 6 It can be seen from the figure that th...

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Abstract

The invention discloses a parallel computing method for Kirchhoff offsets with offset division on multiple GPUs. According to the method, an offset division policy is adopted and the number of threads participating in computing can be increased according to the limitations of GPU memories, so that the multi-computing-core advantages of the GPUs can be brought into full play. The method comprises the following steps of distributing data; calculating an offset range; performing local offset imaging; and generating an imaging gather. According to the method, the number of imaging points for single-GPU computing can be increased as far as possible, the multi-core advantages of the GPUs can be brought into play, the computing efficiency is greatly improved, and a computing result is correct.

Description

technical field [0001] The invention belongs to the technical field of information processing, and in particular relates to a Kirchhoff-type offset parallel calculation method for dividing offset distances on multiple GPUs. Background technique [0002] Prestack migration of seismic data based on Kirchhoff integration has the characteristics of simple principle, stable calculation, strong adaptability, and target-oriented imaging, etc., and is widely used in industrial production. [0003] The calculation principle of Kirchhoff-type imaging can be described as the input seismic trace is calculated according to the travel time, and the amplitude is placed on the imaging point in the imaging aperture. According to the offset of the input data, the output of a single surface imaging point is as follows: figure 1 The offset gather shown in (a), and then stack the offset gather, the result is as follows figure 1 As shown in (b), it finally becomes an imaging profile, such as fi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F9/50
CPCG06F9/5066G06F2209/5017
Inventor 刘国峰李春
Owner BEIJING GEOSTAR SCI & TECH