# Gauss seidel method algorithm

The result of this first iteration of the Gauss-Seidel Method is. x (1) = (x 1 (1) , x 2 (1) , x 3 (1) ) = (0.750, 1.750, − 1.000). We iterate this process to generate a sequence of increasingly better approximations x (0) , x (1) , x (2) , … and find results similar to those that we found for Example 1. Gauss Seidel Iteration Method A simple modification of Jocobi’s iteration sometimes gives faster convergence, the modified method is known as Gauss Seidel method. Let us consider a system of n linear equations with n variables networks are presented for implementations of a Gauss-Seidel algorithm, an improved Gauss-Seidel algorithm and its parallel algorithm running on the Theta cluster processors of High-performance Computing and Simulation Research Lab of University of Florida. We also compare the performance of the three methods