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Forward and adjoint simulations of seismic wave propagation on emerging large-scale GPU architectures

Published: 10 November 2012 Publication History

Abstract

Computational seismology is an area of wide sociological and economic impact, ranging from earthquake risk assessment to subsurface imaging and oil and gas exploration. At the core of these simulations is the modeling of wave propagation in a complex medium. Here we report on the extension of the high-order finite-element seismic wave simulation package SPECFEM3D to support the largest scale hybrid and homogeneous supercomputers. Starting from an existing highly tuned MPI code, we migrated to a CUDA version. In order to be of immediate impact to the science mission of computational seismologists, we had to port the entire production package, rather than just individual kernels. One of the challenges in parallelizing finite element codes is the potential for race conditions during the assembly phase. We therefore investigated different methods such as mesh coloring or atomic updates on the GPU. In order to achieve strong scaling, we needed to ensure good overlap of data motion at all levels, including internode and host-accelerator transfers. Finally we carefully tuned the GPU implementation. The new MPI/CUDA solver exhibits excellent scalability and achieves speedup on a node-to-node basis over the carefully tuned equivalent multi-core MPI solver. To demonstrate the performance of both the forward and adjoint functionality, we present two case studies run on the Cray XE6 CPU and Cray XK6 GPU architectures up to 896 nodes: (1) focusing on most commonly used forward simulations, we simulate seismic wave propagation generated by earthquakes in Turkey, and (2) testing the most complex seismic inversion type of the package, we use ambient seismic noise to image 3-D crust and mantle structure beneath western Europe.

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  1. Forward and adjoint simulations of seismic wave propagation on emerging large-scale GPU architectures

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          cover image ACM Conferences
          SC '12: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
          November 2012
          1161 pages
          ISBN:9781467308045

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          IEEE Computer Society Press

          Washington, DC, United States

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          Published: 10 November 2012

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          SC '12 Paper Acceptance Rate 100 of 461 submissions, 22%;
          Overall Acceptance Rate 1,516 of 6,373 submissions, 24%

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          • (2021)SeisSol on Distributed Multi-GPU Systems: CUDA Code Generation for the Modal Discontinuous Galerkin MethodThe International Conference on High Performance Computing in Asia-Pacific Region10.1145/3432261.3436753(69-82)Online publication date: 20-Jan-2021
          • (2020)Fast Multi-Step Optimization with Deep Learning for Data-Centric SupercomputingProceedings of the 2020 4th International Conference on High Performance Compilation, Computing and Communications10.1145/3407947.3407949(7-13)Online publication date: 27-Jun-2020
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