Abstract
Link based analysis of web graphs has been extensively explored in many research projects. PageRank computation is one widely known approach which forms the basis of the Google search. PageRank assigns a global importance score to a web page based on the importance of other web pages pointing to it. PageRank is an iterative algorithm applying on a massively connected graph corresponding to several hundred millions of nodes and hyper-links. In this paper, we propose an efficient implementation of PageRank computation for a large sub-graph of the web on a PC cluster. A link structure file representing the web graph of several hundred million links, and an efficient PageRank algorithm capable of computing PageRank scores very fast, will be discussed. Experimental results on a small cluster of x86 based PC with artificial 776 million links of 87 million nodes derived from the TH domain report 30.77 seconds per iteration run.
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Rungsawang, A., Manaskasemsak, B. (2003). PageRank Computation Using PC Cluster. In: Dongarra, J., Laforenza, D., Orlando, S. (eds) Recent Advances in Parallel Virtual Machine and Message Passing Interface. EuroPVM/MPI 2003. Lecture Notes in Computer Science, vol 2840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39924-7_24
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DOI: https://doi.org/10.1007/978-3-540-39924-7_24
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