Visualization of level-of-detail meshes on the GPU

Extensive research has been carried out in multiresolution models for many decades. The tendency in recent years has been to harness the potential of GPUs to perform the level-of-detail extraction on graphics hardware. The aim of this work is to present a new level-of-detail scheme based on triangles which is both simple and efficient. In this approach, the extraction process updates vertices instead of indices, thus providing a perfect framework for adapting the algorithms to work completely on GPU shaders. One of the key aspects of our proposal is the need for just a single rendering pass in order to obtain the desired geometry. Moreover, coherence among the different approximations is maximized by means of a symmetric extraction algorithm, which performs the same process when refining and coarsening the mesh. Lastly, we also introduce different uses of the scheme to offer continuous and view-dependent resolution.     

基于GPU编程的地形可视化

由于地形模型固有的复杂性,致使计算机硬件水平一直难以满足大规模地形模型的实时显示需求。为了在现有的硬件水平上实现地形模型的快速绘制,在对传统的ROAM算法进行改进的基础上,提出一种基于GPU编程的地形可视化算法,实现了视点依赖的大规模地形的快速可视化。该算法首先基于改进的ROAM(real-time optimallyadaptive meshes)算法生成视点依赖的优化连续LOD模型;然后用GPU编程计算顶点的变换、法向量、纹理坐标、纹理采样和面元光照;最后完成地形的着色。实验结果表明,利用GPU编程不仅能有效提高算法速度,而且能实现较大规模地形的实时漫游。     

Stardust: Accessible and Transparent GPU Support for Information Visualization Rendering

Web‐based visualization libraries are in wide use, but performance bottlenecks occur when rendering, and especially animating, a large number of graphical marks. While GPU‐based rendering can drastically improve performance, that paradigm has a steep learning curve, usually requiring expertise in the computer graphics pipeline and shader programming. In addition, the recent growth of virtual and augmented reality poses a challenge for supporting multiple display environments beyond regular canvases, such as a Head Mounted Display (HMD) and Cave Automatic Virtual Environment (CAVE). In this paper, we introduce a new web‐based visualization library called Stardust, which provides a familiar API while leveraging GPU's processing power. Stardust also enables developers to create both 2D and 3D visualizations for diverse display environments using a uniform API. To demonstrate Stardust's expressiveness and portability, we present five example visualizations and a coding playground for four display environments. We also evaluate its performance by comparing it against the standard HTML5 Canvas, D3, and Vega.     

Automatic Band-Limited Approximation of Shaders Using Mean-Variance Statistics in Clamped Domain

In this paper, we present a new shader smoothing method to improve the quality and generality of band-limiting shader programs. Previous work [YB18] treats intermediate values in the program as random variables, and utilizes mean and variance statistics to smooth shader programs. In this work, we extend such a band-limiting framework by exploring the observation that one intermediate value in the program is usually computed by a complex composition of functions, where the domain and range of composited functions heavily impact the statistics of smoothed programs. Accordingly, we propose three new shader smoothing rules for specific composition of functions by considering the domain and range, enabling better mean and variance statistics of approximations. Aside from continuous functions, the texture, such as color texture or normal map, is treated as a discrete function with limited domain and range, thereby can be processed similarly in the newly proposed framework. Experiments show that compared with previous work, our method is capable of generating better smoothness of shader programs as well as handling a broader set of shader programs.     

GPU环境下加速移动对象可视化更新的方法研究

移动对象数据具有规模大、更新频繁的特点,对数据可视化具有较高的性能要求。当数据规模增大时,实时加载数据进行可视化的性能效率会随之降低。为了提高移动对象可视化的效率,提出了GPU环境下的移动对象更新方法,并结合移动对象特征设计出并行查询方案。同时,优化了移动对象的更新函数,通过比较临近的两次可视化查询的时间区间,找出需要更新的时间片,对其进行相应的更新,从而避免了整个时间区间的更新。实验使用了数据规模为400万到1 000万的合成数据集,和包含约960万个采样点的真实出租车数据集。实验结果表明,与CPU上的R-Tree查询、GPU上的R-Tree查询和CPU上更新函数中的串行索引查询方法相比,所提方法具有较好的查询性能,加速比最高可达18.48。移动对象更新函数优化后,当临近的两次可视化查询时间区间完全重叠时,加速效率接近100%。     

Zippy: A Framework for Computation and Visualization on a GPU Cluster

Due to its high performance/cost ratio, a GPU cluster is an attractive platform for large scale general‐purpose computation and visualization applications. However, the programming model for high performance general‐purpose computation on GPU clusters remains a complex problem. In this paper, we introduce the Zippy frame‐work, a general and scalable solution to this problem. It abstracts the GPU cluster programming with a two‐level parallelism hierarchy and a non‐uniform memory access (NUMA) model. Zippy preserves the advantages of both message passing and shared‐memory models. It employs global arrays (GA) to simplify the communication, synchronization, and collaboration among multiple GPUs. Moreover, it exposes data locality to the programmer for optimal performance and scalability. We present three example applications developed with Zippy: sort‐last volume rendering, Marching Cubes isosurface extraction and rendering, and lattice Boltzmann flow simulation with online visualization. They demonstrate that Zippy can ease the development and integration of parallel visualization, graphics, and computation modules on a GPU cluster.     

GPU在实时阴影绘制中的应用

实时阴影在增强三维场景真实感方面起着非常重要的作用。阴影体算法是实时阴影绘制中效果非常理想的一种方法。但是随着场景复杂度的增加,该算法计算量比较大,将导致绘制效率的降低。另一方面,随着可编程GPU技术的发展,GPU的渲染速度远远大于CPU,为提高三维场景的渲染效率提供了更大的空间。在此基础上,介绍了一种在GPU上生成阴影体的方法,加速实时阴影绘制。利用图形硬件的图形处理单元（GPU）的运算能力和可编程性,将生成阴影体的大量计算从CPU转移到GPU,从而有效地提高实时阴影的绘制效率。     

Making Shaders More Physically Plausible

There is a need to develop shaders that not only “look good”, but are more physically plausible. From physical and geometric considerations, we review the derivation of a shading equation expressing rejected radiance in terms of incident radiance and the bidirectional reflectance distribution function (BRDF). We then examine the connection between this equation and conventional shaders used in computer graphics. Imposing the additional physical constraints of energy conservation and Helmholtz reciprocity allows us to create variations of the conventional shaders that are more physically plausible.     

基于CUPTI接口的典型GPU程序负载特征分析

基于图形处理器(graphics processing unit, GPU)加速设备的高性能计算机已经成为目前高性能计算领域的一个重要发展趋势.然而,在当前的GPU设备上开发高效的并行程序仍然是一件非常复杂的事情.针对这一问题,1)总结了影响GPU程序性能的5类关键性能指标;2)采用NVIDIA公司提供的CUPTI底层接口,设计并实现了一套GPU程序性能分析工具集,该工具集可以有效地分析GPU程序的性能行为;3)采用该工具集对著名的GPU评测程序集Rodinia中的17个程序和一个真实应用程序进行了负载特征分析.总结出常见性能瓶颈的典型原因,并给出一些开发高效GPU程序的建议.     

Interference Shaders of Thin Films

This paper presents a systematic study of light interferences at single thin films. Based on Fresnel's law, we have derived generic expressions of reflectance and transmittance for film interference, as well as specific expressions for free thin films and films coated on transparent or opaque objects. By combining film interference and volume absorption, we have obtained the reflectances and transmittances of film‐coated thin objects such as ribbons. Illumination models for all interference cases of single thin films are presented, and they have been implemented and tested for various structures and materials.     

一种超图的区域型可视化方法

针对超图绘制中超边表达困难、绘制算法复杂的问题,提出一种超图的快速可视化方法.该方法将超边节点沿其走势线垂线方向向两侧扩展,获得超边中各节点的扩展点;对扩展点根据位置关系重新组合,使用Catmull-Rom算法连接各扩展点,获得超边表示区域的平滑边界曲线;将超边表示区域划分为对偶子段和独立子段,并分别使用三角带和三角扇模式填充;最后根据色相环理论对超边表示区域进行着色,以增强各条超边的区分度.实验结果表明,文中方法能够对超图数据结构进行快速可视化,使用闭合区域包围所有超边节点,从而实现直观、有效的超边表示;对于100个节点/30条超边以内的超图,该方法的绘制效率能够满足实时交互的要求.     

GPU在复杂场景的阴影绘制中的应用

通过有效利用图形硬件的图形处理单元（GPU）的运算能力和可编程性，将人量计算从CPU分离出来。在GPU上采用顶点和片元程序进行阴影计算，从而加速复杂场景阴影绘制。选择图像空间阴影算法进行GPU加速绘制。用Cg图形编程语言和OpenGL实现了算法的绘制过程，能够满足通用的复杂3D场景应用的需要，达到满意的实时绘制效果。     

使用GPU编程的光线投射体绘制算法

将传统的光线投射体绘制算法在具有可编程管线的图形处理器(GPU)上重新实现.首先将体数据作为三维纹理保存在显存中,然后通过编写顶点程序和片段程序将光线进入点/离开点计算和光线遍历的计算移入GPU中执行,最后根据不同的采样点颜色混合公式实现不同的绘制效果.文中算法仅需绘制一个四边形即可完成三维重建.实验结果表明:在进行光照效果的重建时,该算法能够达到实时交互的绘制要求,并能实现半透明等复杂绘制效果.     

Towards Automatic Band‐Limited Procedural Shaders

Procedural shaders are a vital part of modern rendering systems. Despite their prevalence, however, procedural shaders remain sensitive to aliasing any time they are sampled at a rate below the Nyquist limit. Antialiasing is typically achieved through numerical techniques like supersampling or precomputing integrals stored in mipmaps. This paper explores the problem of analytically computing a band‐limited version of a procedural shader as a continuous function of the sampling rate. There is currently no known way of analytically computing these integrals in general. We explore the conditions under which exact solutions are possible and develop several approximation strategies for when they are not. Compared to supersampling methods, our approach produces shaders that are less expensive to evaluate and closer to ground truth in many cases. Compared to mipmapping or precomputation, our approach produces shaders that support an arbitrary bandwidth parameter and require less storage. We evaluate our method on a range of spatially‐varying shader functions, automatically producing antialiased versions that have comparable error to 4×4 multisampling but can be over an order of magnitude faster. While not complete, our approach is a promising first step toward this challenging goal and indicates a number of interesting directions for future work.     

基于GPU的COONS曲面片加速计算

随着可编程图形处理单元(GPU)性能的增强,许多基于GPU的三维几何造型系统的应用也与日俱增。Coons曲面片作为三维建模中重要的基本单元,在农作物的建模仿真以及曲面造型中是重要的。为了适应于GPU的通用计算,对传统Coons曲面片方程进行分解,从而并行构造出Coons曲面片。通过实验表明,随着插值点数的增加,片元程序执行的时间依然保持一定程度的稳定,并没有出现明显的增加;GPU上执行时间的增长速度明显低于在CPU上的增长速度。     

基于GPU的现代并行优化算法

针对现代优化算法在处理相对复杂问题中所面临的求解时间复杂度较高的问题,引入基于GPU的并行处理解决方法。首先从宏观角度阐释了基于计算统一设备架构CUDA的并行编程模型,然后在GPU环境下给出了基于CUDA架构的5种典型现代优化算法(模拟退火算法、禁忌搜索算法、遗传算法、粒子群算法以及人工神经网络)的并行实现过程。通过对比分析在不同环境下测试的实验案例统计结果,指出基于GPU的单指令多线程并行优化策略的优势及其未来发展趋势。     

Using VisTrails and Provenance for Teaching Scientific Visualization

Over the last 20 years, visualization courses have been developed and offered at universities around the world. Many of these courses use established visualization libraries and tools (e.g. VTK, ParaView, AVS, VisIt) as a way to provide students a hands‐on experience, allowing them to prototype and explore different visualization techniques. In this paper, we describe our experiences using VisTrails as a platform to teach scientific visualization. VisTrails is an open‐source system that was designed to support exploratory computational tasks such as visualization and data analysis. Unlike previous scientific workflow and visualization systems, VisTrails provides a comprehensive provenance management infrastructure. We discuss how different features of the system, and in particular, the provenance information have changed the dynamics of the Scientific Visualization course we offer at the University of Utah. We also describe our initial attempts at using the provenance information to better assess our teaching techniques and student performance.     

基于GPU平台的有效字典压缩与解压缩技术

压缩技术被广泛应用于数据存储和传输中,然而由于其内在的串行特性,大多数已有的基于字典的压缩与解压缩算法被设计在CPU上串行执行。为了探究使用图形处理器（graphic processing unit,GPU）对压缩与解压缩过程潜在性能的提升,结合合并内存访问与并行组装的技术,基于CUDA（compute unified device archi-tecture）平台研究了两种并行压缩与解压缩方法：基于字典的无状态压缩和基于字典的LZW压缩。实验结果表明,与传统的单核实现比较,所提方法能够显著改善已有的基于字典的串行压缩与解压缩算法的性能。     

Information Visualization Evaluation Using Crowdsourcing

Visualization researchers have been increasingly leveraging crowdsourcing approaches to overcome a number of limitations of controlled laboratory experiments, including small participant sample sizes and narrow demographic backgrounds of study participants. However, as a community, we have little understanding on when, where, and how researchers use crowdsourcing approaches for visualization research. In this paper, we review the use of crowdsourcing for evaluation in visualization research. We analyzed 190 crowdsourcing experiments, reported in 82 papers that were published in major visualization conferences and journals between 2006 and 2017. We tagged each experiment along 36 dimensions that we identified for crowdsourcing experiments. We grouped our dimensions into six important aspects: study design & procedure, task type, participants, measures & metrics, quality assurance, and reproducibility. We report on the main findings of our review and discuss challenges and opportunities for improvements in conducting crowdsourcing studies for visualization research.