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Proceedings Paper

Reconfigurable visual computing architecture for extreme-scale visual analytics
Author(s): Simon Su; J. Michael Barton; Michael An; Vincent Perry; Brian Panneton; Luis Bravo; Rajgopal Kannan; Venkateswara Dasari
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Paper Abstract

Major advancements in computational and sensor hardware have enormously facilitated the generation and collection of research data by scientists - the volume, velocity and variety of Big ’Research’ Data has increased across all disciplines. A visual analytics platform capable of handling extreme-scale data will enable scientists to visualize unwieldy data in an intuitive manner and guide the development of sophisticated and targeted analytics to obtain useable information. Reconfigurable Visual Computing Architecture is an attempt to provide scientists with the ability to analyze the extreme-scale data collected. Reconfigurable Visual Computing Architecture requires the research and development of new interdisciplinary technological tools that integrate data, realtime predictive analytics, visualization, and acceleration on heterogeneous computing platforms. Reconfigurable Visual Computing Architecture will provide scientists with a streamlined visual analytics tool.

Paper Details

Date Published: 9 May 2018
PDF: 8 pages
Proc. SPIE 10652, Disruptive Technologies in Information Sciences, 106520M (9 May 2018); doi: 10.1117/12.2303887
Show Author Affiliations
Simon Su, U.S. Army Research Lab. (United States)
J. Michael Barton, U.S. Army Research Lab. (United States)
Michael An, U.S. Army Research Lab. (United States)
Vincent Perry, U.S. Army Research Lab. (United States)
Brian Panneton, U.S. Army Research Lab. (United States)
Luis Bravo, U.S. Army Research Lab. (United States)
Rajgopal Kannan, U.S. Army Research Lab. (United States)
Venkateswara Dasari, U.S. Army Research Lab. (United States)

Published in SPIE Proceedings Vol. 10652:
Disruptive Technologies in Information Sciences
Misty Blowers; Russell D. Hall; Venkateswara R. Dasari, Editor(s)

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