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Title: Extreme Scaling of Production Visualization Software on Diverse Architectures

Abstract

We present the results of a series of experiments studying how visualization software scales to massive data sets. Although several paradigms exist for processing large data, we focus on pure parallelism, the dominant approach for production software. These experiments utilized multiple visualization algorithms and were run on multiple architectures. Two types of experiments were performed. For the first, we examined performance at massive scale: 16,000 or more cores and one trillion or more cells. For the second, we studied weak scaling performance. These experiments were performed on the largest data set sizes published to date in visualization literature, and the findings on scaling characteristics and bottlenecks contribute to understanding of how pure parallelism will perform at high levels of concurrency and with very large data sets.

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
Computational Research Division
OSTI Identifier:
983268
Report Number(s):
LBNL-3403E
TRN: US201014%%446
DOE Contract Number:  
DE-AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
IEEE Computer Graphics and Applications
Additional Journal Information:
Journal Volume: 30; Journal Issue: May/June 2010; Related Information: Journal Publication Date: 4/26/2010
Country of Publication:
United States
Language:
English
Subject:
97; ALGORITHMS; PERFORMANCE; PROCESSING; PRODUCTION; ultrascale visualization, parallel visualization, VisIt, extreme scale visualization

Citation Formats

Childs, Henry, Pugmire, David, Ahern, Sean, Whitlock, Brad, Howison, Mark, Weber, Gunther, and Bethel, E Wes. Extreme Scaling of Production Visualization Software on Diverse Architectures. United States: N. p., 2009. Web.
Childs, Henry, Pugmire, David, Ahern, Sean, Whitlock, Brad, Howison, Mark, Weber, Gunther, & Bethel, E Wes. Extreme Scaling of Production Visualization Software on Diverse Architectures. United States.
Childs, Henry, Pugmire, David, Ahern, Sean, Whitlock, Brad, Howison, Mark, Weber, Gunther, and Bethel, E Wes. 2009. "Extreme Scaling of Production Visualization Software on Diverse Architectures". United States. https://www.osti.gov/servlets/purl/983268.
@article{osti_983268,
title = {Extreme Scaling of Production Visualization Software on Diverse Architectures},
author = {Childs, Henry and Pugmire, David and Ahern, Sean and Whitlock, Brad and Howison, Mark and Weber, Gunther and Bethel, E Wes},
abstractNote = {We present the results of a series of experiments studying how visualization software scales to massive data sets. Although several paradigms exist for processing large data, we focus on pure parallelism, the dominant approach for production software. These experiments utilized multiple visualization algorithms and were run on multiple architectures. Two types of experiments were performed. For the first, we examined performance at massive scale: 16,000 or more cores and one trillion or more cells. For the second, we studied weak scaling performance. These experiments were performed on the largest data set sizes published to date in visualization literature, and the findings on scaling characteristics and bottlenecks contribute to understanding of how pure parallelism will perform at high levels of concurrency and with very large data sets.},
doi = {},
url = {https://www.osti.gov/biblio/983268}, journal = {IEEE Computer Graphics and Applications},
number = May/June 2010,
volume = 30,
place = {United States},
year = {Tue Dec 22 00:00:00 EST 2009},
month = {Tue Dec 22 00:00:00 EST 2009}
}