RealGraphGPU: A Convenient and Efficient GPU-Based Graph Analysis Platform on the Web

Jeong-Min Park, Myung-Hwan Jang, Sang-Wook Kim

Abstract: In this demo paper, we present RealGraphGPUWeb a web-based graph analysis platform with the following features: (1) easy to use user-friendly GUI, (2) high processing performance, (3) various graph algorithms and data formats supported, (4) high accessibility anywhere on the web, and (5) no coding requirements. In our demo, we show how a naive user (e.g., non-CS researcher) gets graph analysis results conveniently and efficiently with a few clicks through the web-based GUI inRealGraphGPUWeb. We also make the user feel the effect of performance improvement obtained by our optimization strategies employed in RealGraphGPUWeb. We believe that RealGraphGPUWeb could be a good platform not only for CS users but also for non-CS users who want to analyze big graphs for their applications easily and efficiently.