An extended set of FORTRAN basic linear algebra subprograms
ACM Transactions on Mathematical Software (TOMS)
LAPACK Users' guide (third ed.)
LAPACK Users' guide (third ed.)
Using modern graphics architectures for general-purpose computing: a framework and analysis
Proceedings of the 35th annual ACM/IEEE international symposium on Microarchitecture
Simulation of cloud dynamics on graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
A multigrid solver for boundary value problems using programmable graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Linear algebra operators for GPU implementation of numerical algorithms
ACM SIGGRAPH 2003 Papers
Sparse matrix solvers on the GPU: conjugate gradients and multigrid
ACM SIGGRAPH 2003 Papers
OpenGL(R) Shading Language
A survey of surgical simulation: applications, technology, and education
Presence: Teleoperators and Virtual Environments
Brook for GPUs: stream computing on graphics hardware
ACM SIGGRAPH 2004 Papers
Understanding the efficiency of GPU algorithms for matrix-matrix multiplication
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Computer Animation and Virtual Worlds - Special Issue: The Very Best Papers from CASA 2004
Quick-CULLIDE: Fast Inter- and Intra-Object Collision Culling Using Graphics Hardware
VR '05 Proceedings of the 2005 IEEE Conference 2005 on Virtual Reality
GPU Accelerated Surgical Simulators for Complex Morphology
VR '05 Proceedings of the 2005 IEEE Conference 2005 on Virtual Reality
Computer Animation and Virtual Worlds - CASA 2005
LU-GPU: Efficient Algorithms for Solving Dense Linear Systems on Graphics Hardware
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Rapid pairwise intersection tests using programmable GPUs
The Visual Computer: International Journal of Computer Graphics
EGVE'05 Proceedings of the 11th Eurographics conference on Virtual Environments
Exploring Parallel Algorithms for Volumetric Mass-Spring-Damper Models in CUDA
ISBMS '08 Proceedings of the 4th international symposium on Biomedical Simulation
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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