We present a stationary iterative scheme for PageRank computation. The algorithm is based on a linear system formulation of the problem, uses inner/outer iterations, and amounts to a simple preconditioning technique. It is simple, can be easily implemented and parallelized, and requires minimal storage overhead. Convergence analysis shows that the algorithm is effective for a crude inner tolerance and is not particularly sensitive to the choice of the parameters involved. Numerical examples featuring matrices of dimensions up to approximately 107 confirm the analytical results and demonstrate the accelerated convergence of the algorithm compared to the power method. Key words. PageRank, power method, stationary method, inner/outer iterations, damping factor AMS subject classifications. 65F10, 65F15, 65C40
Andrew P. Gray, Chen Greif, Tracy Lau