Graphics processing unit based parallelization of the distinct lattice spring model

Abstract This study reports a Graphics Processing Unit (GPU)-based parallelization of the Distinct Lattice Spring Model (DLSM) for geomechanics simulation. The DLSM is a newly developed numerical model for rock dynamics problems, i.e., dynamic failure and wave propagation. Despite its applicability, one of the drawbacks of this model is the high computational load for practical simulations. To tackle this problem, a GPU with a Compute Unified Device Architecture (CUDA) is adopted to parallelize the DLSM code. The performance of the GPU DLSM code is tested on two computers equipped with modern GPU cards. The results show that significant performance improvements are gained from GPU parallelization of the DLSM code (the maximum speed up achieved was 23×).

[1]  Hitoshi Gotoh,et al.  GPU-acceleration for Moving Particle Semi-Implicit method , 2011 .

[2]  Jani Sainio.  CUDAEASY - a GPU accelerated cosmological lattice program , 2010, Comput. Phys. Commun..

[3]  Rüdiger Westermann,et al.  A real-time multigrid finite hexahedra method for elasticity simulation using CUDA , 2011, Simul. Model. Pract. Theory.

[4]  Antonio J. Rueda Ruiz,et al.  Parallel drainage network computation on CUDA , 2010, Comput. Geosci..

[5]  Klaus Schulten,et al.  GPU-accelerated molecular modeling coming of age. , 2010, Journal of molecular graphics & modelling.

[6]  Yan Zhang,et al.  GPU simulations for risk assessment in CO2 geologic sequestration , 2011, Comput. Chem. Eng..

[7]  Jian Zhao,et al.  Dynamic Fracturing Simulation of Brittle Material using the Distinct Lattice Spring Method with a Full Rate-Dependent Cohesive Law , 2010 .

[8]  Eric Darve,et al.  Large calculation of the flow over a hypersonic vehicle using a GPU , 2008, J. Comput. Phys..

[9]  N. C. Podlich,et al.  Application of GPU computing to upper bound rigid block analysis , 2011 .

[10]  Gordon Erlebacher,et al.  High-order finite-element seismic wave propagation modeling with MPI on a large GPU cluster , 2010, J. Comput. Phys..

[11]  T. Takahashi,et al.  GPU‐accelerated boundary element method for Helmholtz' equation in three dimensions , 2009 .

[12]  Gao-Feng Zhao,et al.  Development of Micro-Macro Continuum-Discontinuum Coupled Numerical Method , 2010 .

[13]  Karol Miller,et al.  Real-Time Nonlinear Finite Element Computations on GPU - Application to Neurosurgical Simulation. , 2010, Computer methods in applied mechanics and engineering.

[14]  Jiannong Fang,et al.  A 3D distinct lattice spring model for elasticity and dynamic failure , 2011 .

[15]  Wei Ge,et al.  Quasi-real-time simulation of rotating drum using discrete element method with parallel GPU computing , 2011 .

[16]  Jian Zhao,et al.  Validation study of the distinct lattice spring model (DLSM) on P-wave propagation across multiple parallel joints , 2011 .

[17]  John Silberholz,et al.  Black Hole Simulations with CUDA , 2011 .

[18]  Xiaoqian Zhu,et al.  CPU/GPU computing for long-wave radiation physics on large GPU clusters , 2012, Comput. Geosci..

[19]  Peter Bailey,et al.  Accelerating geoscience and engineering system simulations on graphics hardware , 2009, Comput. Geosci..

[20]  Chun Feng,et al.  A GPU Accelerated Continuous-Based Discrete Element Method for Elastodynamics Analysis , 2011 .

[21]  Joshua A. Anderson,et al.  General purpose molecular dynamics simulations fully implemented on graphics processing units , 2008, J. Comput. Phys..