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Real-time nonlinear finite element computations on GPU – Application to neurosurgical simulation

Grand R. Joldes, Adam Wittek, Karol Miller
Intelligent Systems for Medicine Laboratory, School of Mechanical Engineering, The University of Western Australia, Perth, Australia
Computer Methods in Applied Mechanics and Engineering (09 July 2010)

@article{joldes2010real,

   title={Real-time nonlinear finite element computations on GPU-application to neurosurgical simulation},

   author={Joldes, G.R. and Wittek, A. and Miller, K.},

   journal={Computer Methods in Applied Mechanics and Engineering},

   issn={0045-7825},

   year={2010},

   publisher={Elsevier}

}

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Application of biomechanical modeling techniques in the area of medical image analysis and surgical simulation implies two conflicting requirements: accurate results and high solution speeds. Accurate results can be obtained only by using appropriate models and solution algorithms. In our previous papers we have presented algorithms and solution methods for performing accurate nonlinear finite element analysis of brain shift (which includes mixed mesh, different non-linear material models, finite deformations and brain-skull contacts) in less than a minute on a personal computer for models having up to 50.000 degrees of freedom. In this paper we present an implementation of our algorithms on a Graphics Processing Unit (GPU) using the new NVIDIA Compute Unified Device Architecture (CUDA) which leads to more than 20 times increase in the computation speed. This makes possible the use of meshes with more elements, which better represent the geometry, are easier to generate, and provide more accurate results.
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