GPU accelerated computation of the isogeometric analysis stiffness matrix
A novel approach, amenable to parallelization, is proposed for assembling the stiffness matrix. Processing power of GPUs is used to accelerate computations. The GPU implementation of the proposed approach manages to outperform the other approaches by orders of magnitude.
gpu acceleration isogeometric analysis gauss quadrature nurbs stiffness matrix assembly parallel computing