Parallel algorithm implementation for sparse matrix

Parallel algorithm implementation for sparse matrix


This paper describes the Gauss-Jordan method of calculating inverse matrices. An analysis of several papers on a similar topic is described, and the ways of performing the parallelization of Gauss-Jordan method for calculating inverse matrices. The achieved results of the related works are considered. An analysis of technologies suitable for parallel implementation of the calculation of inverse matrices of a rare type was performed, and the reasons why the CUDA platform is selected. Finally, the expected goals of the work itself are described.


Graphics processing unit, Compute unified development architecture, Matrix inversion, Gauss Jordan, Parallelization.

Saračević Kenan
Department of Computing and Informatics
Faculty of Electrical Engineering
University of Sarajevo
Sarajevo, Bosnia and Herzegovina

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