Transfer Function Design for Scientific Discovery

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As computation scales beyond terascale, the scientific problems under study through computing are increasingly pushing the boundaries of human knowledge about the physical world. It is more pivotal than ever to quickly and reliably extract new knowledge from these complex simulations of ultra scale. In this project, the PI expanded the traditional notion of transfer function, which maps physical quantities to visual cues via table look-ups, to include general temporal as well as multivariate patterns that can be described procedurally through specialty mini programming languages. Their efforts aimed at answering a perpetual question of fundamental importance. That is "what a ... continued below

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2.5 MB

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Huang, Jian December 8, 2008.

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Description

As computation scales beyond terascale, the scientific problems under study through computing are increasingly pushing the boundaries of human knowledge about the physical world. It is more pivotal than ever to quickly and reliably extract new knowledge from these complex simulations of ultra scale. In this project, the PI expanded the traditional notion of transfer function, which maps physical quantities to visual cues via table look-ups, to include general temporal as well as multivariate patterns that can be described procedurally through specialty mini programming languages. Their efforts aimed at answering a perpetual question of fundamental importance. That is "what a visualization should show". Instead of waiting for application scientists to initiate the process, the team at University of Tennessee worked closely with scientists at ORNL in a proactive role to envision and design elegant, powerful, and reliable tools that a user can use to specify "what is interesting". Their new techniques include visualization operators that revolve around correlation and graph properties, relative patterns in statistical distribution, temporal regular expressions, concurrent attribute subspaces and traditional compound boolean range queries. The team also paid special attention to ensure that all visualization operators are inherently designed with great parallel scalability to handle tera-scale datasets in both homogeneous and heterogeneous environments. Success has been demonstrated with leading edge computational science areas include climate modeling, combustion and systems genetics.

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2.5 MB

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  • Report No.: NONE
  • Grant Number: FG02-04ER25610
  • DOI: 10.2172/943522 | External Link
  • Office of Scientific & Technical Information Report Number: 943522
  • Archival Resource Key: ark:/67531/metadc902642

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • December 8, 2008

Added to The UNT Digital Library

  • Sept. 27, 2016, 1:39 a.m.

Description Last Updated

  • Jan. 9, 2018, 9:23 a.m.

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Huang, Jian. Transfer Function Design for Scientific Discovery, report, December 8, 2008; Knoxville, Tennessee. (digital.library.unt.edu/ark:/67531/metadc902642/: accessed May 26, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.