In this project, we are studying parallel and distributed processing techniques for managing large-scale graphs. Such graphs are becoming increasingly common in application domains like social network analytics, web graph analysis, bioinformatics, etc. These graphs can be highly dynamic, very large, or both dynamic and large. We investigate system-level as well as analytic techniques for addressing resulting challenges.
In this project, we look at system level techniques to improve performance of BSP style (Pregel-like) graph processing infrastructures on shared memory processors (SMPs).
In this project, we look at incremental maintenance of important graph structures (such as k-core, k-truss, etc.) in the presence of dynamic changes to the graph in a distributed setup (for very large graphs).
TBA