Abstract
Analyzing static snapshots of massive, graph-structured data cannot keep pace with the growth of social networks, financial transactions, and other valuable data sources. We introduce a framework, STING (Spatio-Temporal Interaction Networks and Graphs), and evaluate its performance on multicore, multisocket Intel ® -based platforms. STING achieves rates of around 100 000 edge updates per second on large, dynamic graphs with a single, general data structure. We achieve speedups of up to 1000× over parallel static computation, improve monitoring a dynamic graph’s connected components, and show an exact algorithm for maintaining local clustering coefficients performs better on Intel-based platforms than our earlier approximate algorithm.
Henning Meyerhenke
Professor
David A. Bader
Distinguished Professor, Associate Dean for Research, and Director of the Institute for Data Science
David A. Bader is a Distinguished Professor in the Department of Data Science and Associate Dean for Research in the Ying Wu College of Computing at New Jersey Institute of Technology.
