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A fast way of developing, prototyping and deploying numerical algorithms that can take advantage of CUDA capable systems is available in Mathematica 8. Over the past year, educators, scientists, and business users have taken advantage of the benefits that the support of GPU programming in Mathematica. By integrating and implementing CUDA/OpenCL in their programs, users make use of a hybrid approach, combining the speed-up that GPUs offer and a powerful numerical development system. In this presentation several examples describing numerical applications ranging from deconvolution of MRI imaging, linear solvers for FEM, systems of ODEs, line integral convolution visualization are presented.
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