VISUALIZATION: Integrated Compression and Out-of-Core Techniques for Large Time-Varying Data Visualization

可视化：用于大型时变数据可视化的集成压缩和核外技术

• 批准号: 0118915
• 负责人: Yi-Jen Chiang
• 金额: $ 38.2万
• 依托单位: Polytechnic University of New York
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-15 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0118915&HistoricalAwards=false
• 关键词: VISUALIZATION; Integrated; Compression; Out; Core

Scientific Visualization is fast becoming a key technology that provides scientists with insights that enable them to steer their numerical simulations towards solving previously unsolvable problems. However, the size of scientific datasets has witnessed exponential growth in the past few years. This sheer size often makes interactive exploration impossible, as only a small portion of data can fit into main memory at a time and the computation cost is often too high to run in real-time. Despite the importance of time-varying datasets, most previous research has focused on the visualization of steady-state data (i.e., data with only a single time step). This project will attack the challenges of large input sizes posed by time-varying data visualization. There are two important and promising research directions towards handling large-scale problems: data compression techniques and out-of-core techniques. This project will develop integrated lossless compression and out-of-core techniques for large time-varying data visualization, including isosurface extraction and direct volume rendering. It will mainly consider the class of irregular-grid volume datasets represented as tetrahedral meshes, which often arises in computational fluid dynamics, partial differential equation solvers, and other fields.Specifically, the project will develop new lossless compression techniques for vertex coordinates and scalar values for tetrahedral time-varying volume data. It will also develop new out-of-core isosurface extraction and direct volume rendering techniques for tetrahedral time-varying volume data, and integrate the compression and out-of-core visualization techniques together under a unified infrastructure. The expected results would be a collection of new techniques and a unified, proof-of-the-concept visualization system that will minimize the disk space requirement and the visualization rendering time cost. If successful, the system will efficiently support full visualization functionalities (isosurface extraction and volume rendering) for time-varying datasets much larger than can fit in main memory, with performance expected to be independent of the main memory size available.

科学可视化正在迅速成为一项关键技术，为科学家提供见解，使他们能够引导数值模拟解决以前无法解决的问题。然而，科学数据集的规模在过去几年中呈指数级增长。这种巨大的规模通常使得交互式探索变得不可能，因为一次只能容纳一小部分数据到主内存中，并且计算成本通常太高而无法实时运行。尽管时变数据集很重要，但之前的大多数研究都集中在稳态数据（即仅具有单个时间步长的数据）的可视化上。该项目将应对时变数据可视化带来的大输入量的挑战。处理大规模问题有两个重要且有前途的研究方向：数据压缩技术和核外技术。该项目将开发用于大型时变数据可视化的集成无损压缩和核外技术，包括等值面提取和直接体积渲染。它将主要考虑以四面体网格表示的不规则网格体积数据集，这种数据集经常出现在计算流体动力学、偏微分方程求解器和其他领域。具体来说，该项目将开发新的顶点坐标和标量值无损压缩技术用于四面体时变体积数据。它还将为四面体时变体积数据开发新的核外等值面提取和直接体积渲染技术，并将压缩和核外可视化技术集成在统一的基础设施下。预期结果将是一系列新技术和一个统一的概念验证可视化系统，该系统将最大限度地减少磁盘空间需求和可视化渲染时间成本。如果成功，系统将有效地支持比主内存容量大得多的时变数据集的完整可视化功能（等值面提取和体积渲染），并且性能预计与可用主内存大小无关。