Fast Parallel PageRank: A Linear System Approach
نویسندگان
چکیده
In this paper we investigate the convergence of iterative stationary and Krylov subspace methods for the PageRank linear system, including the convergence dependency on teleportation. We demonstrate that linear system iterations converge faster than the simple power method and are less sensitive to the changes in teleportation. In order to perform this study 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.
منابع مشابه
Robust Fuzzy Gain-Scheduled Control of the 3-Phase IPMSM
This article presents a fuzzy robust Mixed - Sensitivity Gain - Scheduled H controller based on the Loop -Shaping methodology for a class of MIMO uncertain nonlinear Time - Varying systems. In order to design this controller, the nonlinear parameter - dependent plant is first modeled as a set of linear subsystems by Takagi and Sugeno’s (T - S) fuzzy approach. Both Loop - Shaping methodology and...
متن کاملFast ranking algorithm for very large data
In this paper, we propose a new ranking method inspired from previous results on the diffusion approach to solve linear equation. We describe new mathematical equations corresponding to this method and show through experimental results the potential computational gain. This ranking method is also compared to the well known PageRank model. Keywords-Large sparse matrix, Iteration, Fixed point, Pa...
متن کاملEuler-Richardson method preconditioned by weakly stochastic matrix algebras: a potential contribution to Pagerank computation
Let S be a column stochastic matrix with at least one full row. Then S describes a Pagerank-like random walk since the computation of the Perron vector x of S can be tackled by solving a suitable M-matrix linear system Mx = y, where M = I − τA, A is a column stochastic matrix and τ is a positive coefficient smaller than one. The Pagerank centrality index on graphs is a relevant example where th...
متن کاملAn Inner-Outer Iteration for Computing PageRank
We present a new iterative scheme for PageRank computation. The algorithm is applied to the linear system formulation of the problem, using inner-outer stationary iterations. It is simple, can be easily implemented and parallelized, and requires minimal storage overhead. Our convergence analysis shows that the algorithm is effective for a crude inner tolerance and is not sensitive to the choice...
متن کاملFast PageRank Computation via a Sparse Linear System
Recently, the research community has devoted increased attention to reducing the computational time needed by web ranking algorithms. In particular, many techniques have been proposed to speed up the well-known PageRank algorithm used by Google. This interest is motivated by two dominant factors: (1) the web graph has huge dimensions and is subject to dramatic updates in terms of nodes and link...
متن کامل