A cloud-enabled remote visualization tool for time-varying climate data analytics. (January 2016) - Zhang, Tong; Li, Jing; Liu, Qing; Huang, Qunying
Abstract: The ever-growing time-varying climate datasets pose challenges for efficient analytics using the current desktop-based or generic remote visualization tools. We present a tightly-coupled scalable cloud-enabled remote visualization tool that exploits the computational capabilities of Graphical Processing Units (GPUs). We implement three typical volumetric/3D visualization techniques to illustrate the enhanced performance offered by remote GPU clusters. Our development also enables fast deployment to facilitate the access of remote analytics tools by a wide range of end users. Highlights: We present a cloud-enabled remote visualization tool for climate data analytics. We introduce a light-weight deployment solution based on pre-configured cloud images. Three volume visualization techniques were implemented in the tool using remote GPU clusters.