Code Synthesis for High-Performance Graph Analytics

Graph analytics platforms are widely deployed across diverse domains to analyze large, unstructured and semi-structured data-sets. The ability to process large data-sets quickly is especially important in the domain of cyber security where detecting sophisticated attacks in a timely manner is crucially important for maintaining network security.While existing tools are clearly effective, there is a persistent need to perform deeper analyses on larger data-sets and retrieve information more quickly. Graphics processors (GPUs) have the potential to deliver dramatically better performance but realizing that potential necessitates algorithms and data-structures tailored to the target device. Specializing algorithms by hand is impractical and prohibitively expensive. We propose to build a tool for generating specialized, high-performance graph algorithms for GPUs starting from high-level Python code.The tool will leverage an existing analytics framework to yield an integrated, high-productivity, high-performance graph analytics capability.