HPC Enabled Immersive and non-Immersive Visualization of Large Scale Scientific Data

摘要

Advancement in the areas of high performance computing and computational sciences have facilitated the generation ofan enormous amount of research data by computational scientists - the volume, velocity and variability of Big 'Research'Data has increased across all disciplines. An immersive and non-immersive analytics platform capable of handlingextreme-scale scientific data will enable scientists to visualize unwieldy simulation data in an intuitive manner and guidethe development of sophisticated and targeted analytics to obtain usable information. Our immersive and non-immersivevisualization work is an attempt to provide computational scientists with the ability to analyze the extreme-scale datagenerated. The main purpose of this paper is to identify different characteristics of a scientific data analysis process toprovide a general outline for the scientists to select the appropriate visualization systems to perform their data analytics.In addition, we will include some of the details on how to how the immersive and non-immersive visualization hardwareand software are setup. We are confident that the findings in our paper will provide scientists with a streamlined andoptimal visual analytics workflow.