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MRI: Acquisition of a Graphics Supercomputer for Synthetic Environment Serving Science and Engineering

MRI: Acquisition of a Graphics Supercomputer for Synthetic Environment Serving Science and Engineering
MRI:采购图形超级计算机,用于服务于科学与工程的合成环境
批准号:
9871222
负责人:
Henry Fuchs
金额:
$130.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1998
资助国家:
美国
项目状态:
已结题
起止时间:
1998-09-01 至 2001-08-31

项目摘要

项目成果

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中文摘要
翻译
北卡罗来纳州教堂山加里大学亨利·毕晓普的EIA-9871222核磁共振成像:收购一台用于合成环境的图形超级计算机服务科学和工程建议的仪器是一台最先进的实时图形计算机,一种硅图形现实怪物。这款机器将8条高性能图形渲染流水线与32个传统RISC处理器紧密结合在一起。该仪器将加速实时合成环境在科学和工程中的应用研究。这项提案中提出的主要项目是那些非凡的图形能力和紧密结合的高性能计算能力对于在未来三年实现否则不可能的研究进展至关重要的那些项目。这些项目包括:以纳米级渲染世界图像,因为数据来自原子力显微镜;增强现实应用,例如让外科医生使用从体内通过腹腔镜获得的图像深入人体;渲染复杂人造结构的大型模型,如船舶和工厂,用于交互式漫游,以检查结构和做出设计决定;直接从远程真实世界场景的多个图像以及传统几何模型渲染;快速渲染到头戴式或覆盖墙壁的数百万像素的大型显示器;跟踪户外增强现实。
英文摘要
EIA-9871222 Fuchs, Henry Bishop, Gary University of North Carolina Chapel Hill MRI: Acquisition of a Graphics Supercomputer for Synthetic Environments Service Science and Engineering The proposed instrument is a state-of-the-art real-time graphics computer, a Silicon Graphics Reality Monster. This machine intimately combines eight high-performance graphics rendering pipelines with 32 conventional RISC processors. This instrument will accelerate research on real-time synthetic-environments applications in science and engineering. The principal projects set forth in this proposal are those for which both the exceptional graphics power and the intimately coupled high-performance computing power are crucial for enabling otherwise impossible research advances in the next three years. The projects include: rendering images of the world at nanometer scales as data come from atomic-force microscopes; augmented reality for applications such as giving the surgeon a view into the body using the images from inside the body, through a laparoscope; rendering massive models of complex man-made structures, such as ships and factories, for interactive walkthroughs to examine structures and make design decisions; rendering directly from multiple images of remote real-world scenes as well as from traditional geometric models; rapidly rendering to large, multi-megapixel displays either head-mounted or covering the walls; tracking outdoors for augmented reality.
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会议论文
Collaborative Research: HCC: Medium: Deep Learning-Based Tracking of Eyes and Lens Shape from Purkinje Images for Holographic Augmented Reality Glasses
RI: Small: Uncovering Dynamics from Internet Imagery
FW-HTF: Collaborative Research: Enhancing Human Capabilities through Virtual Personal Embodied Assistants in Self-Contained Eyeglasses-Based Augmented Reality (AR) Systems
CHS: Small: Collaborative Research: 3D Audio Augmentation for Limited Field of View Augmented Reality Systems for Medical Training
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