Heuristic Optimization with CPU-GPU Heterogeneous Wave Computing for Estimating Three-Dimensional Inner Structure

To increase the reliability of numerical simulations, it is important to use more reliable models. This study proposes a method to generate a finite element model that can reproduce observational data in a target domain. Our proposed method searches parameters to determine finite element models by combining simulated annealing and finite element wave propagation analyses. In the optimization, we utilize heterogeneous computer resources. The finite element solver, which is the computationally expensive portion, is computed rapidly using GPU computation. Simultaneously, we generate finite element models using CPU computation to overlap the computation time of model generation. We estimate the inner soil structure as an application example. The soil structure is reproduced from the observed time history of velocity on the ground surface using our developed optimizer.

[1]  L. Ingber Very fast simulated re-annealing , 1989 .

[2]  Pher Errol Balde Quinay,et al.  Performance Enhancement of Three-Dimensional Soil Structure Model via Optimization for Estimating Seismic Behavior of Buried Pipelines , 2017 .

[3]  Tsuyoshi Ichimura,et al.  An elastic/viscoelastic finite element analysis method for crustal deformation using a 3-D island-scale high-fidelity model , 2016 .

[4]  Pher Errol Balde Quinay,et al.  Implicit nonlinear wave simulation with 1.08T DOF and 0.270T unstructured finite elements to enhance comprehensive earthquake simulation , 2015, SC15: International Conference for High Performance Computing, Networking, Storage and Analysis.

[5]  Anthony T. Chronopoulos,et al.  s-step iterative methods for symmetric linear systems , 1989 .

[6]  Tsuyoshi Ichimura,et al.  Three-Dimensional Nonlinear Seismic Ground Response Analysis of Local Site Effects for Estimating Seismic Behavior of Buried Pipelines , 2014 .

[7]  Franz Günter Sander,et al.  Quasi-automatic 3D finite element model generation for individual single-rooted teeth and periodontal ligament , 2004, Comput. Methods Programs Biomed..

[8]  Tsuyoshi Ichimura,et al.  Viscoelastic Crustal Deformation Computation Method with Reduced Random Memory Accesses for GPU-Based Computers , 2018, ICCS.

[9]  David Kirk,et al.  NVIDIA cuda software and gpu parallel computing architecture , 2007, ISMM '07.

[10]  Jianwen Liang,et al.  Site Effects on Seismic Behavior of Pipelines: A Review , 2000 .

[11]  Paulius Micikevicius,et al.  3D finite difference computation on GPUs using CUDA , 2009, GPGPU-2.

[12]  Markus H. Gross,et al.  Simulating facial surgery using finite element models , 1996, SIGGRAPH.

[13]  Pher Errol Balde Quinay,et al.  Waveform Inversion for Modeling Three‐Dimensional Crust Structure with Topographic Effects , 2012 .