E-Mail Graphs -- data structures that show the relationship among objects -- are highly versatile. It's easy to imagine a graph depicting a social media network's web of connections. But graphs are also used in programs as diverse as content recommendation (what to watch next on Netflix?) and navigation (what's the quickest route to the beach?). As Ajay Brahmakshatriya summarizes: "graphs are basically everywhere." Brahmakshatriya has developed software to more efficiently run graph applications on a wider range of computer hardware. The software extends GraphIt, a state-of-the-art graph programming language, to run on graphics processing units (GPUs), hardware that processes many data streams in parallel. The advance could accelerate graph analysis, especially for applications that benefit from a GPU's parallelism, such as recommendation algorithms.