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Matrix inversion speed up with CUDA

Jorge Soriano Pinedo
Graduate College, Illinois Institute of Technology
Chicago, Illinois, 2011

@article{soriano2011matrix,

   title={Matrix inversion speed up with CUDA},

   author={Soriano Pinedo, J.},

   year={2011},

   publisher={Universitat Polit{`e}cnica de Catalunya}

}

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In this project several mathematic algorithms are developed to obtain a matrix inversion method – that combines CUDA’s parallel architecture and MATLAB which is actually faster than MATLAB’s built in inverse matrix function. This matrix inversion method is intended to be used for image reconstruction as a faster alternative to iterative methods with a comparable quality. The algorithms developed in this project are Gauss-Jordan elimination, Cholesky decomposition, Gaussian elimination and matrix multiplication. Gauss-Seidel is also featured in the report, but only as an alternative method of finding the inverse, since it has not been developed in the project.
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