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For small matrices, any mathematical package will be managed with an unrestricted arithmetics (protection of all signs to be obtained in the transformation process). It'll be slow, but he'll answer your questions.For large matrices, it's a completely pointless idea, because the memory and time of the bill will grow exponentially.We'll wonder why computer mathematics have been on computers for 60 years and libraries haven't.First, as I've already noticed, it's almost impossible.Secondly, it is not necessary for anyone to do so, as in practice, the recycled system is well known -- in most cases (diffures, interpolation, minimization), it is a square matrix that is more or less legitimized.Hence, the question of improving the dependence of the matrix, first, and the development of the iterative methods of decision-making, second, should be raised.In order to increase conditionality, there are a number of algorithms that, through trivial changes (only reversing lines and columns), increase conditionality by predominating the main diagonal. Realizing these algorithms is in ViennaCL.To date, auction methods, as the most effective, should be identified among the iterative methods. These are methods that build the mooring space - the method of associated gradients, GMRES and their modifications. Their implementation can also be found in ViennaCL.