Scalable scientific data

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Publication Type poster
School or College Scientific Computing and Imaging Institute
Department Computing, School of
Creator Pascucci, Valerio; Swank, William Lorenzo
Title Scalable scientific data
Date 2010-02-26
Description Question Hierarchial Z-Order Evaluation How can we present hundreds or thousands of gigabytes of scientific data to a user for analysis and interpretation? • The Scientific Computing and Imaging Institute is responsible for helping scientists visualize massive amounts of data. • Sources of large scientific data include medical imaging equipment (CAT, PET, MRI, etc.), fluid dynamics simulations, and genetic sequence mapping • Some of these simulations produce hundreds of gigabytes of data per simulation time step. Evaluating the speed of loading a set of random samples from an 8GB 3D image showed that: •Both Z and HZ-order significantly outperform the standard Row Major mode representation •HZ-order also outperforms Z-order for progressive requests Based on the Lebesque curve • Indexes Z-curve resolution levels in hierarchical order from coarser to finer. • Maintains the same geometric locality for each Z-curve resolution level • Beneficial for progressive resolution requests. (e.g. an "object search" application may first attempt to perform filtering on a coarser resolution)
Type Text; Image
Publisher University of Utah
Language eng
Bibliographic Citation Pascucci, V., & Swank, W. L. (2010). Scalable scientific data. University of Utah.
Rights Management (c)Valerio Pascucci, William Lorenzo Swank
Format Medium application/pdf
Format Extent 2,739,048 bytes
Identifier ir-main/14962
ARK ark:/87278/s6000kt9
Setname ir_uspace
Date Created 2012-07-30
Date Modified 2021-05-06
ID 707637
Reference URL https://collections.lib.utah.edu/ark:/87278/s6000kt9
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