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Efficient Level-Crossing Probability Calculation for Gaussian Process Modeled Data 17

Efficient Level-Crossing Probability Calculation for Gaussia...

引用

17th Pacific visualization Conference (PacificVis)

作者： Li, Haoyu Michaud, Isaac J. Biswas, Ayan Shen, Han-Wei Ohio State Univ Columbus OH 43210 USA Los Alamos Natl Lab Los Alamos NM 87545 USA

ISBN: (纸本)9798350393811;9798350393804

Almost all scientific data have uncertainties originating from different sources. Gaussian process regression (GPR) models are a natural way to model data with Gaussian-distributed uncertainties. GPR also has the benefit of reducing I/O bandwidth and storage requirements for large scientific simulations. However, the reconstruction from the GPR models suffers from high computation complexity. To make the situation worse, classic approaches for visualizing the data uncertainties, like probabilistic marching cubes, are also computationally very expensive, especially for data of high resolutions. In this paper, we accelerate the level-crossing probability calculation efficiency on GPR models by subdividing the data spatially into a hierarchical data structure and only reconstructing values adaptively in the regions that have a non-zero probability. For each region, leveraging the known GPR kernel and the saved data observations, we propose a novel approach to efficiently calculate an upper bound for the level-crossing probability inside the region and use this upper bound to make the subdivision and reconstruction decisions. We demonstrate that our value occurrence probability estimation is accurate with a low computation cost by experiments that calculate the level-crossing probability fields on different datasets.

关键词： human-centered computing-visualization-visualization techniques human-centered computing-visualization-visualization application domains-scientific visualization

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A Study of the Locality of Persistence-Based Queries and Its Implications for the Efficiency of Localized Data Structures 15

A Study of the Locality of Persistence-Based Queries and Its...

引用

IEEE 15th Pacific visualization Symposium (PacificVis)

作者： Klacansky, Pavol Gyulassy, Attila Bremer, Peer-Timo Pascucci, Valerio Univ Utah SCI Inst Salt Lake City UT 84112 USA LLNL Livermore CA USA

ISBN: (纸本)9781665423359

scientific datasets are often analyzed and visualized using iso-surfaces. The connected components at or above the isovalue defining these isosurfaces are called superlevel-set components. The vertex set of these superlevel-set components can be used to compute local statistics, such as mean temperature or histogram per component, or to segment the data. However, in datasets produced by acquisition devices or simulations, noise induces many spurious components that clutter the visualization and analysis results. Many of these spurious components would disappear if the data values were slightly adjusted. The notion of persistence captures the stability of a component with respect to function value changes, and so we are interested in computing persistence quickly. Locality of computation is critical for parallel scalability, minimization of communication in a distributed environment, or an out-of-core processing. The recently introduced merge forest attained high performance by exploiting locality, thereby avoiding communication until needed to resolve a feature query. We extend the merge forest to support persistence-based queries and study the locality of these queries by evaluating the traversals of regions of data during a query. We confirm that the majority of evaluated datasets have the property that the noise is mostly local, and thus can be efficiently eliminated without performing a global analysis. Finally, we compare the query running times with those of a triplet merge tree because a triplet merge tree answers all proposed queries in constant time and can be constructed from a merge tree in linear time.

关键词： human-centered computing-visualization-visualization application domains-scientific visualization

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GPU-based Raycasting of Hermite Spline Tubes

GPU-based Raycasting of Hermite Spline Tubes

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IEEE visualization Conference (VIS)

作者： Russig, Benjamin Salm, Mirco Gumhold, Stefan Tech Univ Dresden Dresden Germany

ISBN: (纸本)9781728180144

Visualizing curve and trajectory data is a common task in many scientific fields including medicine and physics. Tubes are an effective visualization primitive for this sort of data, but they require highly specialized renderers to achieve high image quality at frame rates sufficient for interactive visualization. We present a rendering algorithm for Hermite spline tubes, i.e. tubes that result from Hermite splines interpolating the data, with support for varying-radii circular tube cross sections. Our approach employs raycasting and works directly on this continuous representation without the need for surface tessellation, made possible by an efficient ray-tube intersection routine suitable for execution on modern GPUs.

关键词： computing methodologies-Computer graphics-Rendering human-centered computing-visualization-visualization application domains-scientific visualization

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