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Visualization and processing of planetary-scale graphs using vertex-centric high performance techniques

Grant number: 13/03906-0
Support type:Scholarships in Brazil - Master
Effective date (Start): June 01, 2013
Effective date (End): November 30, 2015
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:José Fernando Rodrigues Júnior
Grantee:Hugo Armando Gualdron Colmenares
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated scholarship(s):14/07879-0 - Visually spotting patterns in planetary scale graphs, BE.EP.MS


The so-called planetary-scale (or Web-scale) graphs comprise millions of vertices and billions of edges. Such graphs have appeared in several contemporaneous contexts containing information that can potentially explain social behavior (Twitter and Facebook), commercial activities (Amazon), system structures (like roads and computer networks), non-structured information (Wikipedia), information organization (hypertext), to name a few. These graphs are of great analytical value because, besides having a wide range of information, the current trend is that more of such datasets will appear in the following years. For this reason, it becomes necessary the development and the mastering of techniques capable of working with such volumes of information. In this work, we propose to use vertex-centric techniques and asynchronous parallel processing in order to process and to visually represent planetary-scale graphs. The work will based on system GraphChi within the goals of developing analytic-visual techniques that do not demand computational clusters, but, instead, turn the visualization of large graphs accessible to commercial systems with a single processing node.

Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
COLMENARES, Hugo Armando Gualdron. Block-based and structure-based techniques for large-scale graph processing and visualization. 2015. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação São Carlos.

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