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=== Part 2 ===
With Mr Szalwinski's advice we've starting looking into how to invert a matrix and use NVidia's cuSOLVER library. Our research has shown that by inverting a Matrix we are solving linear system of equations. And if the goal is to solve equations there are better ways of doing so. <br/><br/>
NVidia cuSOLVER library provides hight-level API functions for common matrix factorization and triangular solve routines for dense matrices. While it also provides routines for sparse matrix factorization it lies beyond the scope of this assignment. Our code includes 3 factorization methods on the GPU: LU, QR and Cholesky decomposition as well as LU decomposition on CPU to benchmark the runtimes. <br/><br/>
[[File:file9.png|500px]]
LU stands for Lower & Upper. This methods involves transformation of original matrix into two parts - lower and upper.
