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

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，使他们能够将数值模拟转向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。这种庞大的规模往往使交互式探索成为不可能，因为一次只能将一小部分数据放入主存，而且计算成本往往太高，无法实时运行。尽管时变数据集很重要，但大多数以前的研究都集中在稳态数据的可视化上（即，仅具有单个时间步长的数据）。该项目将解决时变数据可视化带来的大输入规模的挑战。在处理大规模问题方面，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。该项目将开发集成的无损压缩和核外技术，用于大型时变数据可视化，包括等值面提取和直接体绘制。主要研究在计算流体力学、偏微分方程求解器等领域中经常出现的四面体网格表示的不规则网格体数据集，开发适用于四面体时变体数据的顶点坐标和标量值的无损压缩新技术。它还将为四面体时变体数据开发新的核外等值面提取和直接体绘制技术，并将压缩和核外可视化技术集成在统一的基础设施下。预期的结果将是一个新技术的集合和一个统一的，概念验证的可视化系统，将最大限度地减少磁盘空间的要求和可视化渲染的时间成本。如果成功，该系统将有效地支持完整的可视化功能（等值面提取和体绘制）的时变数据集远远大于可以容纳在主存储器，与性能预计将是独立的主存储器大小可用。

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.