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A Scalable System for Enormous Dataset Volume Visualization on Commodity Hardware

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-05-C-0107
Agency Tracking Number: A054-002-0330
Amount: $94,704.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A05-T002
Solicitation Number: N/A
Timeline
Solicitation Year: 2005
Award Year: 2005
Award Start Date (Proposal Award Date): 2005-08-15
Award End Date (Contract End Date): 2006-02-11
Small Business Information
8 E. Broadway, Suite 307, Salt Lake City, UT, 84111
DUNS: 148056281
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 David Weinstein
 Chief Technical Officer
 (801) 328-1100
 dmw@visual-influence.com
Business Contact
 Kirk Mosher
Title: Chief Financial Officer
Phone: (801) 328-1100
Email: kmosher@visual-influence.com
Research Institution
 UNIV. OF UTAH - SCI INSTITUTE
 Elliott Kulakowski
 1471 E Federal Way
Salt Lake City, UT, 84102
 (801) 581-3003
 Nonprofit college or university
Abstract
We are submitting this proposal in response to the call for proposals STTR A05-T002, topic "Distributed Heterogenous Large Data Visualization of Physics Based Simulations". The stated objective of the call is to develop a system capable of generating interactive visualizations of enormous datasets that result from physics-based simulations on US DoD High Performance Computing facilities. Interactive visualization of such datasets poses substantial challenges; researchers have studied the problem of rendering large, complex models at interactive frame rates for many years. Much of this study has been limited to the visualization of scenes composed primarily of polygonal geometry. For more complex scenes composed of structured and unstructured grid datasets, the challenge of interactive visualization is far greater. We propose to meet this challenge by building a prototype of a visualization system based on a foundation of our recent work on visibility computations and out-of-core algorithms, and novel algorithms for rendering large unstructured grids. Our proposed work has two main objectives: 1) to develop a client-server framework for the visualization of large datasets on a single workstation and on a cluster of PCs; and 2) to develop techniques for the interactive exploration of very large structured and unstructured datasets.

* Information listed above is at the time of submission. *

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