VLG1 effort focused on a proof-of-concept demonstration implementing time-dependent graph theory and methods for analyzing very large scale graphs that include temporal dependencies. VLG2 extended the research by studying the impact of uncertainty mechanisms in data on anomalous subgraph detection and to understand and characterize uncertainty in real datasets. VLG-H investigated the advanced hardware system components for processing massive network data two to four orders of magnitude beyond existing capabilities. Specific technical improvements to be explored are data dependent optimization, a high bandwidth communication network, cache-less memory, specialized processing for sparse matrices, low-power circuitry, a sparse array instruction set, and semantic processing.
