Scalable Architecture for Real Time Volume Rendering

用于实时体积渲染的可扩展架构

• 批准号: 9527694
• 负责人: Arie Kaufman
• 金额: $ 56.37万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-10-01 至 1999-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9527694&HistoricalAwards=false
• 关键词: Scalable; Architecture; Real; Time; Volume

This research deals with the development of a new scalable volume visualization architecture and its associated algorithms. The architecture, called Cube-4, exploits parallelism and pipelining to achieve real-time rendering of high-resolution images from volume data. The architecture is based on an algorithm for ray casting of a volume buffer of voxels which is stored as a skewed distributed memory to support conflict-free access to voxel structures. It performs interpolation of sampled points, shading, and compositing to generate the pixel values. Computations are done using limited communication between processors, so that the architecture is scalable over a wide range of performances and image resolutions. This project encompasses algorithm development, architecture research, and construction of a reduced-resolution prototype.

这项研究涉及新的可扩展量可视化体系结构及其相关算法的开发。 该架构称为Cube-4，利用并行性和管道来实现从体积数据中实现高分辨率图像的实时渲染。 该体系结构基于一种用于射线铸造体体积缓冲区的算法，该量子的体积缓冲区被存储为偏斜的分布式内存，以支持对体素结构的无冲突访问。 它执行采样点，阴影和合成的插值以生成像素值。 计算是使用处理器之间的有限通信完成的，因此在各种性能和图像分辨率上，体系结构可扩展。 该项目涵盖了算法开发，建筑研究以及分辨率原型的构建。