Web-Site-Based Partitioning Techniques for Reducing the Preprocessing Overhead before the Parallel PageRank Computations

The efficiency of the PageRank computation is important since the constantly evolving nature of the Web requires this computation to be repeated many times. Due to the enormous size of the Web’s hyperlink structure, PageRank computations are usually carried out on parallel computers. Recently, a hypergraph-partitioning-based formulation for parallel sparse-matrix vector multiplication is proposed as a preprocessing step which will minimize the communication overhead of the parallel PageRank computations. Based on this work, we propose Website-based partitioning approaches in order to reduce the overhead of this preprocessing step. The conducted experiments show that the proposed approach produces comparable performance results for PageRank computation while achieving lower preprocessing overheads.