Provided by: University of Bristol
Date Added: Oct 2012
Graph processing has gained renewed attention. The increasing large scale and wealth of connected data, such as those accrued by social network applications, demand the design of new techniques and platforms to efficiently derive actionable information from large scale graphs. Hybrid systems that host processing units optimized for both fast sequential processing and bulk processing (e.g., GPU-accelerated systems) have the potential to cope with the heterogeneous structure of real graphs and enable high performance graph processing.