So much data, so little time ...

被引：0

作者：

Hansen, C ^{[1
]}

Parker, S ^{[1
]}

Gribble, C ^{[1
]}

机构：

[1] Univ Utah, Sci Comp & Imaging Inst, Salt Lake City, UT 84112 USA

来源：

PARALLEL COMPUTING: SOFTWARE TECHNOLOGY, ALGORITHMS, ARCHITECTURES AND APPLICATIONS | 2004年 / 13卷

关键词：

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Massively parallel computers have been around for the past decade. With the advent of such powerful resources, scientific computation rapidly expanded the size of computational domains.,With the increased amount of data, visualization software strove to keep pace through die implementation of parallel visualization tools and parallel rendering leveraging the computational resources. Tightly coupled ccNUMA parallel processors with attached graphics adapters have shifted the research of visualization to leverage the more unified memory architecture. Our research at the Scientific Computing and Imaging (SCI) Institute at the university of Utah has focused on innovative, scalable techniques for large-scale 3D visualization. Real-time ray-tracing for isosurfacing has proven to be the most interactive method for lame scale scientific data. We have also investigated cluster-based volume rendering leveraging multiple nodes of commodity components.

引用

页码：13 / 20

页数：8

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