There are billions of network events every day. Analyzing these large event graphs is critical for effective cyber defense. However, the sheer amount of events overwhelms existing tools and systems. Graph analytics forms the basis for complex processing on large event graphs to identify anomalies as smaller sub-graphs for exploration. This session will unveil ongoing work for the first capability for end-to-end GPU acceleration of network traffic analysis that accelerates both analytics and visualization. We'll discuss community detection algorithms such as Newman Spectral Modularity and accelerating it with Blazegraph DASL and nvGraph. We'll also demonstrate the first integration with GPU-accelerated visualization (Graphistry) in which an analyst used community detection and graph traversals to successfully discover a network exfiltration.