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.

本文研究了一种新的可伸缩体可视化体系结构及其相关算法的开发。这种名为Cube-4的体系结构利用并行和流水线技术从体数据中实现高分辨率图像的实时渲染。该体系结构基于对体素的体积缓冲区进行光线投射的算法，体素的体积缓冲区被存储为倾斜分布式存储器，以支持对体素结构的无冲突访问。它执行采样点的内插、着色和合成以生成像素值。计算使用处理器之间的有限通信来完成，因此该体系结构可在广泛的性能和图像分辨率范围内扩展。该项目包括算法开发、体系结构研究和降低分辨率原型的构建。