Fast Parallel PageRank: Linear System approach to PageRank Computations
with David Gleich and Pavel Berkhin
In this paper we investigate the convergence of iterative stationary and Krylov subspace methods for the PageRank linear system and study the effect of the teleportation coefficient on its convergence. We demonstrate that linear system converge faster than ''simple'' power iterations method and are less sensitive to the changes in teleportation. In order to perform the experiments we developed a framework for parallel PageRank computing. We describe the details of the parallel implementation and provide experimental results obtained
on a 70-node Beowulf cluster.
Paper: Scalable Computing for Power Law Graphs: Experience with Parallel PageRank
Tex Report: Fast Parallel PageRank: A Linear System Approach
Power Point Presentation: Massively Parallel Scalable PageRank