An Introduction to GPU Accelerated Surgical Simulation

  • Thomas Sangild Sørensen
  • Jesper Mosegaard
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4072)


Modern graphics processing units (GPUs) have recently become fully programmable. Thus a powerful and cost-efficient new computational platform for surgical simulations has emerged. A broad selection of publications has shown that scientific computations obtain a significant speedup if ported from the CPU to the GPU. To take advantage of the GPU however, one must understand the limitations inherent in its design and devise algorithms accordingly. We have observed that many researchers with experience in surgical simulation find this a significant hurdle to overcome. To facilitate the transition from CPU- to GPU-based simulations, we review the most important concepts and data structures required to realise two popular deformable models on the GPU: the finite element model and the spring-mass model.


Memory Bandwidth Conjugate Gradient Algorithm Graphic Hardware Texture Memory Implicit Finite Element 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Thomas Sangild Sørensen
    • 1
  • Jesper Mosegaard
    • 2
  1. 1.Centre for Advanced Visualisation and Interaction 
  2. 2.Department of Computer ScienceUniversity of AarhusDenmark

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