Experimental Study of a Parallel Iterative Solver for Markov Chain Modeling

TL;DR

This paper experimentally evaluates a parallel iterative solver for Markov chain models, demonstrating its effectiveness for block banded systems in parallel computing environments.

Contribution

It introduces a parallel stationary iterative method based on block staircase splitting for solving singular linear systems in Markov chain modeling.

Findings

Effective for block banded systems

Suitable for parallel computing environments

Benchmarked with various Markovian models

Abstract

This paper presents the results of a preliminary experimental investigation of the performance of a stationary iterative method based on a block staircase splitting for solving singular systems of linear equations arising in Markov chain modelling. From the experiments presented, we can deduce that the method is well suited for solving block banded or more generally localized systems in a parallel computing environment. The parallel implementation has been benchmarked using several Markovian models.