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GPU optimization and implementation of Gaussian belief propagation algorithm

We report the utilization of the parallel resources of the graphic processing unit (GPU) to solve sparse systems by optimizing and implementation of a variant of Gaussian belief propagation algorithm for sparse matrices on a Tesla 2070M GPU with the Fermi architecture. The implementation was verified with finite element method data and achieved up to 4× improvement in execution time compared to serial CPU implementation.