A three-dimensional anisotropy elastic wave numerical simulation method and system
A numerical simulation, three-dimensional and all-directional technology, applied in the field of geophysical exploration, can solve problems such as high cost and not widely used, achieve the effect of low hardware cost, optimize communication bottlenecks, and improve overall computing performance
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Embodiment 2
[0068] In Embodiment 2, on the basis of Embodiment 1, the step 4 specifically includes the following steps:
[0069] Step 4.1: Determine the calculation area of each grid point according to all wave field values, and use the absorption boundary method to determine the calculation area boundary, and simulate the wave propagation in the underground medium in the calculation area;
[0070] Step 4.2: Divide all the calculation areas, exchange the boundary data of adjacent divisions, obtain simulated elastic wave data, and complete the elastic wave numerical simulation.
Embodiment 3
[0071] In Embodiment 3, on the basis of Embodiment 1 or 2, the boundary data in step 4.2 adopts GPU-Direct technology for data exchange.
Embodiment 4
[0072] In Embodiment 4, on the basis of any one of Embodiments 1-3, the data exchange in step 4.2 specifically includes:
[0073] Decompose the region along the axis where the data change at the boundary of the computing region in the media model is the slowest to obtain multiple partitions. All partitions are allocated to multiple GPUs. Each partition performs calculations on a GPU independently; every two adjacent partitions The boundary data is exchanged.
[0074] In this embodiment, further, the calculation boundary data of each computing node at each time is implemented using GPU-Direct technology to exchange data as follows:
[0075] When solving large-scale 3D models, the limited global memory makes it impossible for a single GPU device to store the entire model mesh. To this end, our algorithm must extend the CUDA code to run on multi-GPU devices and multi-node heterogeneous architectures to make full use of GPU computing power for high-performance computing. For this reaso...
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