A cloud-enabled remote visualization tool for time-varying climate data analytics. (January 2016)

• Record Type: Journal Article
• Authors: Zhang, Tong; Li, Jing; Liu, Qing; Huang, Qunying
• Is Part Of: Environmental modelling & software. Volume 75(2016:Jan.)
• Page Start: 513
• Page End: 518
• Publication Date: 2016-01
• Subjects: Remote visualization -- Climate data -- Cloud-enabled -- GPU; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.10.033
• Languages: English
• ISSNs: 1364-8152

Abstract

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.