paga:index
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Welcome to the PAGA homepage. | Welcome to the PAGA homepage. | ||
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+ | The goal of this project is to design, implement and evaluate parallel algorithms for large-scale graph analysis. In particular, we are interested in scalable approaches for computing centrality metrics on distributed memory architectures. Centrality metrics such as betweenness centrality, clustering coefficient, | ||
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+ | The PAGA project is supported by an Italian Supercomputing Research Allocation (ISCRA) project HP10CR15I1 from 2012/10/02 to 2013/07/02. PAGA has been granted the use of [[http:// | ||
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+ | === Background === | ||
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+ | A social network can be analyzed by computing appropriate metrics on the underlying graph. Unfortunately, | ||
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+ | Computing centrality metrics in large social graphs is challenging and is subject of active research. However, most of the existing solutions rely on shared memory architectures, | ||
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+ | === State of the art === | ||
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+ | We carried out a fairly complete review of the state of the art in a forthcoming paper: M. Lambertini, M. Magnani, M. Marzolla, D. Montesi, C. Paolino, [[http:// | ||
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+ | === Expected Outcomes === | ||
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+ | Our primary goal is to understand if and how centrality metrics can be effectively computed on distributed memory architectures. A positive answer will be a significant contribution to the research community. Our secondary goal is to laid the foundations for the development of a software package for social network analysis on distributed memory architectures based on MPI. This package should run both on general-purpose, |
paga/index.txt · Last modified: 2013/03/27 12:41 by gdangelo