CAREER: Toward Effective Visualization of Large Scale Time-Varying Data

随着模拟产生的数据量呈指数级增长，计算科学家在过去几年中面临着新的挑战。导致数据量增长的一个主要因素是执行大规模时变模拟的能力日益普及。本项目旨在设计高效的数据处理和有效的特征提取技术，以方便大规模时变数据分析。本研究的具体目标是研究时变可视化算法中的以下基本问题：(1)设计时空数据编码和管理方案，以方便在任意时空尺度上对数据进行运行时浏览和分析；(2)开发加速可视化算法，利用时空数据一致性。感兴趣的主题包括设计空间高效的时变等值面提取算法，多分辨率时变体绘制的自动细节水平算法，负载平衡并行数据分布和可视化方案。(3)设计新颖的时变特征增强和跟踪技术。具体来说，重点是发展新的高维体投影技术，以突出时间相关特征的进展和演变，以及高维几何算法来跟踪时变的轮廓和间隔体积。重点还在于体绘制中有效传递函数的设计，以提取显著的时变特征

New challenges for computational scientists have emerged in the past several years as the size of data generated from simulations has experienced an exponential growth. One major factor that is contributing to the growth of data size is the increasingly widespread ability to perform very large-scale time-varying simulations. This project aims to design efficient data processing and effective feature extraction techniques to facilitate large-scale time-varying data analysis.The specific goal of this research is to study the following fundamental problems in time-varying visualization algorithms: (1) Design spatio-temporal data encoding and management schemes to facilitate run-time browsing and analysis of data at arbitrary spatial and temporal scales, (2) Develop accelerated visualization algorithms to utilize spatial and temporal data coherence. Topics of interest include the design of space-efficient time-varying isosurface extraction algorithms, automatic level of detail algorithms for multi resolution time-varying volume rendering, and load balanced parallel data distribution and visualization schemes, (3) Design novel time-varying feature enhancement and tracking techniques. Specifically, focus is on the development of novel high dimensional volume projection techniques to highlight the progression and evolution of time-dependent features, and high dimensional geometric algorithms to track time varying is contours and interval volumes. Focus is also on the design of effective transfer functions used in volume rendering to extract salient time-dependent features