Merging Jacobi and Gauss-Seidel methods for solving Markov chains on computer clusters
Jarosław Bylina, Beata Bylina · 2008
The authors consider the use of the parallel iterative methods for solving large sparse linear equation systems resulting from Markov chains-on a computer cluster. A combination of Jacobi and Gauss-Seidel iterative methods is examined in a parallel version. Some results of experiments for sparse systems with over 3 times 107equations and about 2 times 108nonzeros which we obtained from a Markovian model of a congestion control mechanism are reported.