Abstract
PageRank is a prominent metric used by search engines for ranking of search results. Page rank of a particular web page is a function of page ranks of all the web pages pointing to this page. The algorithm works on a large number of web pages and is thus computational intensive. The need of hardware is currently served by connecting thousands of computers in cluster. But faster and less complex alternatives to this system can be found in multi-core processors. In this paper, we identify major issues involved in porting PageRank algorithm on Cell BE Processor and CUDA, and their possible solutions. The work is evaluated on three input graphs of different sizes ranging from 0.35 million nodes to 1.3 million. Our results show that PageRank algorithm runs 2.8 times fast on CUDA compared to Xeon dual core 3.0 GHz.
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References
Brin, S., Page, L.: The Anatomy of a Large-Scale Hypertextual Web Search Engine. In: Proceedings of the 7th International World Wide Web Conference, Brisbane, Australia, pp. 107–117 (April 1998)
Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: Bringing order to the web. Stanford Digital Library Working Paper (1998)
PageRank Google’s Original Sin, http://www.google-watch.org/pagerank.html
Haveliwala, T.H.: Topic Sensitive PageRank. IEEE Transactions on Knowledge and Data Engineering 15(4), 784–796 (2003)
Chen, Y.Y., Gan, Q., Suel, T.: I/O-efficient techniques for computing PageRank. In: Proceedings of the Eleventh International Conference on Information and Knowledge Management, McLean, Virginia, USA, pp. 549–557 (2002)
Kamvar, S.D., Haveliwala, T.H., Manning, C.D., Golub, G.H.: Exploting the block Structure of the Web for Computing PageRank. Technical Report CSSM-03-02, Computer Science Department, Stanford University (2003)
Manaskasemsak, B., Rungsawang, A.: Parallel PageRank Computation on gigabit PC Cluster. In: Proceedings of 18th International Conference on Advanced Information Networking and Applications AINA, Fukuoka Japan, vol. 1, pp. 273–277 (March 2004)
Buehrer, G., Parthasarathy, S., Goyder, M.: Data mining on the cell broadband engine. In: Proceedings of the 22nd Annual International Conference on Supercomputing, Island of Kos, Greece, pp. 26–35 (June 2008)
Cell Broadband Engine – An introduction. Cell Programming Workshop, IBM System and Technology Group, April 14-18 (2007)
Sarje, A., Aluru, S.: Parallel Genomic Alignments on the Cell Broadband Engine. IEEE Transactions on Parallel and Distributed Systems, December 09 (2008)
Kurzak, J., Buttari, A., Dongarra, J.: Solving Systems of Linear Equations on the CELL Processor Using Cholesky Factorization. IEEE Transactions on Parallel and Distributed Systems 19(9), 1175–1186 (2008)
Liu, W., Schmidt, B., Voss, G., Muller-Wittig, W.: Streaming Algorithms for Biological Sequence Alignment on GPUs. IEEE Transactions on Parallel and Distributed Systems 18(9), 1270–1281 (2007)
Garland, M., Le Grand, S., Nickolls, J., Anderson, J., Hardwick, J., Morton, S., Phillips, E., Zhang, Y., Volkov, V.: Parallel Computing Experiences with CUDA. IEEE Micro 28(4), 13–27 (2008)
Laboratory for Web Algorithmics, http://law.dsi.unimi.it/index.php?option=com_include&Itemid=65
Boldi, P., Codenotti, B., Santini, M., Vigna, S.: UbiCrawler: A Scalable Fully Distributed Web Crawler. Journal of Software: Practice & Experience 34, 711–726 (2004)
User guide, Cell buzz, http://wiki.cc.gatech.edu/cellbuzz/index.php/User_Guide
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Kumar, T., Sondhi, P., Mittal, A. (2012). Parallelization of PageRank on Multicore Processors. In: Ramanujam, R., Ramaswamy, S. (eds) Distributed Computing and Internet Technology. ICDCIT 2012. Lecture Notes in Computer Science, vol 7154. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28073-3_12
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DOI: https://doi.org/10.1007/978-3-642-28073-3_12
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