Abstract
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 107 equations and about 2 times 108 nonzeros which we obtained from a Markovian model of a congestion control mechanism are reported.
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